OCTOBER 1981
LIDS-R-1157
SYSTEMS ARCHITECTURE AND EVALUATION
Edited By
Michael Athans
Wilbur B. Davenport, Jr.
Elizabeth R. Ducot
Robert R. Tenney
Proceedings of the Fourth MIT/ONR Workshop on
Distributed Information and Decision Systems
Motivated by Command-Control-Communications (C 3) Problems
Volume II
June 15 - June 26, 1981
San Diego, California
ONR Contract No. N00014-77-C-0532
PREFACE
This volume is one of a series of four reports containing contributions from the speakers at the fourth MIT/ONR Workshop on Distributed
Information and Decision Systems Motivated by Command-Control-Communication
(C3 ) Problems.
Held from June 15 through June 26, 1981 in San Diego,
California, the Workshop was supported by the Office of Naval Research
under contract ONR/N00014-77-C-0532 with MIT.
The purpose of this annual Workshop is to encourage informal interactions between university, government, and industry researchers on basic
issues in future military command and control problems.
It is felt that
the inherent complexity of the C 3 system requires novel and imaginative
thinking, theoretical advances and the development of new basic methodologies in order to arrive at realistic, reliable and cost-effective designs for future C3 systems.
Toward these objectives, the speakers, in
presenting current and future needs and work in progress, addressed the
following broad topics:
1)
Surveillance and Target Tracking
2)
Systems Architecture and Evaluation
3)
Communication, Data Bases & Decision Support
4)
C 3 Theory
In addition to the Workshop speakers and participants, we would
like to
thank Dr. Stuart Brodsky
of the Office of Naval Research, and
Ms. Barbara Peacock-Coady and Ms. Lisa Babine of the MIT Laboratory for
Information and Decision Systems for their help in making the Workshop
a success.
Cambridge,
MichaeZ Athans
Massachusetts
October 1981
Wilbur B. Davenport, Jr.
Elizabeth R. Ducot
Robert R. Tenney
-1-
SYSTEM ARCHITECTURE AND
FOREWORD
..
EVALUATION
..............................................
iv
3
C I SYSTEMS EVALUATION PROGRAM
Dr. Stuart H. Starr ......................................
C
1
SYSTEM RESEARCH AND EVALUATION: A SURVEY AND ANALYSIS
Dr. David S. AZberts ..................................... 21
THE INTELLIGENCE ANALYST PROBLEM
Dr. Daniel Schutzer ..........................
..............
31
DERIVATION OF AN INFORMATION PROCESSING SYSTEMS (C /MIS)
--ARCHITECTURAL MODEL -- A MARINE CORPS PERSPECTIVE
Lieutenant CoZoneZ James V. Bronson ..........................
67
A CONCEPTUAL CONTROL MODEL FOR DISCUSSING COMBAT DIRECTION
SYSTEM (C2). ARCHITECTURAL ISSUES
Dr. Timothy Kraft and Mr. Thomas Murphy ..................... 93
EVALUATING THE UTILITY OF JINTACCS MESSAGES
Captain John S. Morrison .....................................
109
FIRE SUPPORT CONTROL AT THE FIGHTING LEVEL
Mr. Barry L. Reichard ....................................... 131
A PRACTICAL APPLICATION OF MAU IN PROGRAM DEVELOPMENT
Major James R. Hughes ........
.............
.............
165
HIERARCHICAL VALUE ASSESSMENT IN A TASK FORCE DECISION ENVIRONMENT
Dr.
Ami ArbeZ ............
-ii-
.............
............. 191
OVER-THE-HORIZON, DETECTION, CLASSIFICATION AND TARGETING
(OTH/DC&T) SYSTEM CONCEPT SELECTION USING FUNCTIONAL FLOW
DIAGRAMS
Dr. GZenn E. Mitzel ......................................... 211
A SYSTEMS APPROACH TO COMMAND, CONTROL AND COMMUNICATIONS
SYSTEM DESIGN
Dr. Jay K. Beam and Mr. George D. HaZuschynsky .............. 227
MEASURES OF EFFECTIVENESS AND PERFORMANCE FOR YEAR 2000
TACTICAL C3 SYSTEMS
Dr. Djimitri Wiggert ........................................ 243
AN END USER FACILITY
COMMUNICATIONS (C3 )
(EUF) FOR COMMAND, CONTROL, AND
Drs. Jan D. Wald and Sam R. HoZZllingsworth ................... 261
SYSTEM ARCHITECTURE AND
EVALUATION
FOREWORD
While the other three volumes of these proceedings deal with theorectical
or algorithmic aspects of C , the papers of this volume address the more
3
realistic, and clearly quite important, issue of structuring a C system
to maximize its abilities to support a military mission.
The design of
C 3 systems involves both (a) the conception of functional organizations
which deliver the right information to the right decision makers at the
right time, and
(b) the evaluation of those organizations in terms of
overall mission effectiveness, not specific performance characteristics
of individual elements.
The emphasis in C 3 design must be to make the
symphony as a whole sound good, not to require virtuoso performances from
each player in isolation.
The papers in this section are grouped according to four major themes:
overview and general perspective
3
(1-4), discussions of existing C systems
(5-7), evaluation of hierarchically structured systems
(8-9), and frame-
works for C3 design based on functional decomposition and analysis
(10-13).
This organization reflects both the variety of perspectives one can take,
3
and the lack of a unified, consistant framework in which C architecture
can be considered.
Of the first group, Starr and AZberts provide broad overviews of ongoing programs in this area.
In contrast, Schutzer and Bronson
conceptual frameworks for addressing some generic C
intelligence analysis and Marine Corps applications,
describe
issues motivated by
Kraft-Murphy leads
the transition to specific problems in a discussion of the Navyts Advanced
Combat Direction System architecture, and
Morrison and Reichard discuss the
utility and content of information communicated in Air Force and Army applications.
On the evaluation side, one needs a methodology for relating the performance of elementary equipment modules, as measured by their engineering
-iv-
specifications, to the overall mission effectiveness.
Hughes gives a
case study of one such methodology; Arbel discusses some of the theoretical issues encountered in such analyses.
the nascent effort at Johns-Hopkins
Finally, several papers from
(APL) (Mitzel, Beam-HaZuschynsky,
Wiggert) and HoneyweZZ (Waid) bring these same issues to bear on design
problems.
_V_
C
I SYSTEMS
EVALUATION
BY
Stuart H. Starr
The Pentagon
Washington, DC 20301
1
PROGRAM
C I SYSTEMS EVALUATION PROGRAM
by
Dr. Stuart H. Starr
ABSTRACT
The accompanying annotated briefing describes the objectives of
3
the Systems Evaluation directorate in C I. The presentation summarizes the goals of the office, describing on-going initiatives, and
identifying major problem areas that require additional work.
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20
J
C
SYSTEM RESEARCH AND EVALUATION:
A
SURVEY AND ANALYSIS
BY
David S. AZberts
The MITRE Corporation
1820 DoZZey Madison BZlvd.
McLean, Virginia 22102
21
C
SYSTEM RESEARCH AND EVALUATION:
A SURVEY AND ANALYSIS
ABSTRACT
The Assistant Secretary of Defense (C
3I) has, during the past year,
established a new Directorate in his organization to develop and implement
DoD-wide initiatives related to the quantitative analysis and evaluation
of C3 systems.
As initial steps in the development of this program, MITRE
has conducted a survey and analysis of selected DoD-sponsored systems research and evaluation activities and established a C3 Systems Research and
Evaluation Library.
The Abstract and Executive Summary for both documents
Readers may obtain
on which this presentation are based are attached.
these documents by contacting the following individuals:
For:
C
Systems Research and Evaluation:
Survey & Analysis
John Gasparotti
The MITRE Corporation
M. S. W354
1820 Dolley Madison Boulevard
McLean, VA 22102
For:
C
Systems Research and Evaluation Library
D. W. Hodge
The MITRE Corporation
M.S. W375
1820 Dolley Madison Boulevard
McLean, VA 22102
22
TITLE:
C3Systems Research and Evaluation Library
AUTHOR:
Diana W. Hodge
DOCUMENT NO:
MTR 80W00357
ABSTRACT:
This document describes the C3I Research and Evaluation
Library, a computer aided data storage and retrieval
system which includes a data base containing C 3 I related
(1) an overview of the method
documents. It provides:
for categorizing and assigning identified codes to each
document in the data base; (2) instructions for using
the C3 I Library's data retrieval system which locates
documents and prints out pertinent document information;
(3) appendices containing indices for manual document
retrieval when a computer is unavailable to the user;
and (4) a biblio raphy of the documents acquired in
support of the C I research and evaluation project.
23
Executive Summary
compact form in Table I (Code Reference Sheet). The
data classification system for coding each document
entry is explained in the section entitled "Data
Classification."
In addition to providing the capability of selecting
document entries by subject area code, the data
retrieval system is planned to have provisions for
searching by title, author, corporate author, document
number, sponsor, date, point-of-contact, and
keywords such as subjects and names, or any other
information contained in the entry, including the document abstract. Again, this is done in a simple English
format generally by entering instructions to search for
the item of information sought
For those readers without access to the computer
based retrieval system, three appendices are provided.
Appendix A is an "Index for Document Retrieval by
Categories" in which all documents are listed by entry
number. For each entry, the applicable categories and
codes are indicated. By searching along any category
row(s), the entries corresponding to that category or
combination of categories may be found. Appendix B
is an "Index for Document Retrieval by Authors"
where document entries are sorted by individual author. The entries themselves are found in Appendix C,
"Bibliography of All Document Data Entries." There,
computer printouts of the entry data for each document in the library are reproduced in entry number
order. By this means, the entry data (including abstracts) for any documents located by a search using
the index may be examined to determine if the
document itself is applicable to the researcher's needs
and to identify it and its source. Both the category
index and the bibliography are in entry number order
so that new entries may be added as additional
documents are received and processed into the
system.
The C31 Library at present contains enough document entries to show its abilities but is by no means allinclusive. Readers are invited to submit appropriate
documents for inclusion in the library by completing
the form at the end of this document
The Command, Control, Communications, and Intelligence (C31) Research and Evaluation Library is a
computer-aided data storage and retrieval system. The
library was created in support of MITRE's C31 Systems
Research and Evaluation Project sponsored by the
Office of the Assistant Secretary of Defense, OASD
(C31). This document is intended as a guide to understanding the system of categories used to retrieve
document information that is of interest for specific
purposes, and as a user's manual containing procedures for using the C3I Library's data retrieval, review,
and print capabilities.
Each document entry in the library has its title,
document number, date, security classification, author(s), corporate author, sponsor, agency, and pointof-contact identified. In addition, the content of the
document has been categorized by codes indicating
the subject activity, mission area addressed, service
agency concerned, purpose or anticipated use for the
activity or methodology presented, its place in the
spectrum of research and evaluation techniques, the
C31 system component(s) discussed, the methods of
evaluation used or presented, and the current status of
the subject activity as of the date of the document.
These codes may be used to select those documents in
the library relating to any subject area or combination
of subject areas of interest. Each document entry also
contains a short abstract to provide the user further
insight as to its suitability for his particular purpose.
The document identification information is stored in
an interactive data storage and retrieval system using
the IBM System/370 MITRE computer. User access to
the system will be established in January 1981. Document entries relating to a specific area of interest may
be retrieved by entering the appropriate identifier
code, or combination of codes, so that entries corresponding to those categories will be selected and
displayed on the computer terminal and/or printed.
This selection process is simple: the user responds to
clear English language instructions and options offered
by the program. No knowledge of computers or the
data retrieval system is required beyond that of the
appropriate code numbers, which are supplied in
24
TITLE:
C3 Systems Research and Evaluation:
AUTHOR:
John Gasparotti (Principal Author), Diana Hodge
DOCUMENT NO:
MTR 80W00356
ABSTRACT:
This document contains the results of a survey of
activities and organizations engaged in research and
evaluation of command, control, and communications
(C3 ) systems. The distribution of such activities
among the services and agencies of the Department of
Defense is examined, as well as the relationships and
connectivity of activities and organizations. Principal areas of interest include how the activities
contribute to research in C 3 theory, assessment, and
development; as well as methods and measures being
used to evaluate C 3 systems. Finally, the activities
are examined as to their contribution to the overall
DoD wide program of C3 systems research and evaluation.
Positive attributes and initiatives as well as areas
of concern are concluded.
25
Survey and Analysis
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THE
INTELLIGENCE
ANALYST PROBLEM
BY
Daniel Schutzer
Chief of Naval Operations
Naval Intelligence
NOP 009T
Washington DC 20350
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The Intelligence Analyst Problem - Dr. Daniel Schutzer
1. The intelligence analysts job is to provide information of
military significance to the decision maker regarding the enemies
movements, capabilities, plans and intentions.
The decision maker
,should not be overwhelmed with all manner of minutiae regarding
the enemy.
Rather his attention should be focussed on key items
of interest. Key items validate, amplify, or cast in doubt preThey reveal enemy
vailing hypothesis concerning the enemy.
strengths and vulnerabilities which may be exploited or countered.
They represent information that cause the decision maker to take
actions.
The intelligence analyst derives his knowledge from information collected from uncooperative sources.
He predicts future
enemy plans and capabilities from scant, incomplete information
concerning past historical patterns and current activity and plans.
33
2. Over the past decade three changes have occurred that both
complicate and add importance to the intelligence analysts function.
The relative military strength of our adversary has increased
dramatically both in quality and quantity. Our technological
leadership has eroded to the point that in many areas other countries
not only equal our capability but exceed it.
Finally, the nature of warfare has increased orders of magnitude
in its tempo and sophistication. Warfare has become faster paced.
Today's weapons are more lethal and more capable. These weapons
are equipped with a bewildering array of sophisticated sensors,
alternate modes of operation, and countermeasures to confuse and
defeat the enemy. They strike and faint rapidly given their opponent
little time to react and counter.
This all makes it more critical than ever for our decision makers
to be armed with good timely intelligence.
But, at the same time,
this intelligence task of compiling and providing quality intelligence has become much more difficult.
The enemy doesn't merely mirror our capabilities and tactics.
The situation is not static,
On many fronts he leads and innovates.
it is changing with increasing frequency. To further complicate
the problem, the enemy is quite adapt at playing the information
war. He both denies us key information and deceives us with false
information.
To overcome these difficulties, we build ever more capable
information collection systems. And, our "take" of data increases
both in detail and quantity.
But, to a great extent, this further compounds the problem.
Data comes in by the bucketful, but, it comes uncorrelated with
important gaps and flaws. And, the analysts burden of compiling,
relating, processing, and reducing this collected data to timely,
useful intelligence increases in magnitude.
Currently, this task is man-power intensive, strongly dependent
It is
upon the skill and insight of the individual analyst.
analogous to how the great Sherlock Holmes succeeds in piecing
together seemingly disconnected clues to solve a mystery.
This talk argues that there is a systematic methodology underlying the intelligence analyst task.
And, that once found and
made explicit, this systematic methodology will both enable the
analyst to do his job better and will allow for automation to
relieve the analyst of much of his workload in more fundamental
ways than would otherwise be .possible.
So long as the intelligence analysts task remains highly
individualistic and unsystematized, automation can only minimially
alleviate the analysts workload. It can only be used to aid him
34
in his secondary activities such as editing, producing, and delivering messages and reports, displaying and producing pictures and
graphics, storing and retrieving data, and the like. It is believed
that the introduction of a systematic methodology will enable
automation to be more directly applied to the primary activities
of the intelligence analysts, resulting in much greater gains in
analyst productivity.
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3. I submit that the intelligence process can be modelled as
shown in this viewgraph.
Data is collected, transformed and interpreted in terms of
one or more hypotheses that the analyst has consciously or
unconsciously formulated with respect to the enemy actions and
intentions which he is concerned.
The collected data is used to confirm, refine, and update his
,current prevailing hypotheses; to select among several competing
hypotheses; and/or to formulate new hypotheses.
These hypotheses are then projected and extrapolated to evaluate
and interpret future collected data.
Once a hypothesis is formed a drastic reduction of data can take
place prior to any significant-processing. Only data items directly
relevant to the hypothesized models need to be analyzed and retained.
All other data elements can be filtered out.
It is the thesis of this talk
intelligence analyst problem, the
those that are needed to maintain
models shown: Sensor, situation,
interaction, organization.
that, in the case of the
only relevant data elements are
the five knowledge base data
event history, timeline-
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4. These knowledge base models are related or linked to one
another.
The major data elements and their various interdependencies
are illustrated in this viewgraph.
These dependencies can be used to crosscheck and verify
a data element entry.
They will often times suggest what
value a currently unobserved data element should possess.
The specifics of these five data models, their data elements,
,and their interdependencies form, in essence, an explicit representation of an analysts hypothesis.
It should be noted. that although this viewgraph emphasizes
the enemys military warfighting capability, the same approach
can be taken to understand and project the enemies science and
technology capabilities of their R&D establishment or a civil
terrorist organization.
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5. To illustrate let us consider the case of a strike mission
against ships either in transit or at port. For this example
we will concentrate on the operational aspects peculiar to the
mission: Namely, the organization and the timeline - interaction
models and their major data elements shown here. Once these
two models are established, the sensor model and the event history
model are determined by the detailed physical characteristics and
capabilities of the sensors and platforms involved. The current
situation is scenario-dependent and will not be discussed here.
41
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6. For the strike example it is assuemd that there are only three
organizational levels involved. Namely Fleet, Flotilla, and unit
level. And, three type units are involved: Submarine, aircraft and
ASW surface ship.
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7. A nominal operational sequence for the strike mission example
is illustrated here. The mission is broken down into its component
functions. These functions are related to one another in terms of
their interdependencies and their relative ordering with respect to
time. It should be noted here that this example is purely illustrative in nature. The functions shown are not necessarily inclusive
or in sufficient detail. The nominal times cannot be substantiated
or validated. It should be noted that the nominal times assigned
to a particular function are not necessarily a single valued constant
They may be more properly represented by a random
quantity.
variable or a permissible range. Finally, although illustrated
in a flow chart format, this same information can be readily represented in a table format more adoptable to computer storage and
retrieval.
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previous viewgraph, these functions may be allocated among the
various organizational elements and units. One such functional
allocation is illustrated here.
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9. This next data element deals with a very significant issue.
It is assumed that any organizational entity assigned a function to
perform has associated with that assigned function an objective.
This objective may only be implicit. But even if the executing
organization is not consciously aware of it, it unconsciously
bases its response and approach to the execution of its assigned
Implied in this association of
task to some underlying objectives.
is the belief that the
function
with
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behavior of that organizational element in the execution of
its assigned task can be represented by an appropriative
normative optimizer or satisfier process. This process includes
the interaction or output response of the organization to its
inputs. An example of such a set of objectives for the strike
In real life, these objectives
mission is shown in this viewgraph.
may only be approximated by a more practical or expeditiously
In the interest of simplicity
implementable normative process.
or time, or conservation of resources, the actual process may only
seek an adequate solution from out of an acceptable set as opposed
to a single optimum solution. In fact, the selection of a specific
solution from the acceptable solution set may be best represented
by a random process (e.g. some statistic game theoretic solutions.)
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The interaction model represents for each organizational
element:
Its memory or knowledge base; its assigned functions; and,
for each assigned function, the required inputs and applicable
responses. Clearly, the normative process for an organizational
element can be derived from its assigned functions, their associated
objectives and their interaction model.
The next three viewgraphs illustrate examples of an interactive model for the Fleet Headquarters, Submarine Flotilla and
submarine organizational entities for the strike example.
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Now let us explore how application of this systematic methodology
to the intelligence analyst process might lead to more effective aids.
I believe that this methodology aids the analyst by more consciously
arranging his knowledge base in a formal explicit representation such as
the five data models suggested in this talk (i.e.; sensor, current
situation, event, timeline/interaction, organization).
By adding such
discipline to the process we make more evident to the analyst what his
hypotheses are.
This should help to focus his attention and to make
·more apparent which are the data items most deserving of his attention.
This structure should make more obvious where the important
gaps and inconsistencies in his knowledge base remain.
It should
highlight where the important collection requirements are.
Explicit
representation of this process should make possible a more comprehensive
approach to automation and the introduction of analyst aids than would
otherwise be possible.
A great deal more of the data reduction and
evaluation tasks can now be automated.
We know how to transform and
associate the data with respect to the specific knowledge base models.
A great deal of irrelevant and/or redundant data can be recognized
automatically and filtered out reducing the information overload/
saturation currently experienced by the analysts while minimizing the
likelihood that key data will be overlooked. Another benefit is that
once formulated and stored in a computer, an alternative hypothesis
will not be forgotten or overlooked. A computer will not forget.
All
viable hypothesis will be continually stored, updated, and compared
as to applicability. Furthermore, a computer is free of any human
bias.
It has no favorite hypothesis.
If a secondary hypothesis
suddenly becomes a primary candidate based upon new data, this
unexpected change will be caught and brought to the attention of
the analyst.
Likewise, if a favorite hypothesis begins to lose its
viability as the result of new data and changing situations, this
unhappy fact will also be persistently pointed out to the analyst.
Examples of how this methodology may be applied to aid the
analyst process is illustrated with three generic examples.
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In example 1, it can be shown that the functional allocations
can be derived from complete knowledge of the organizational
structure, the organizational objectives and their interactions.
Knowledge of this data and the actual communications, sensors,
and weapons systems technology employed determine the operational
sequence timeline.
Thus starting with complete knowledge of the
organizational structures, objectives and interactions, a hypotheses
can be completely substantiated.
Other known data model elements
can be used to check consistency and validity.
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13. Complete knowledge of the organizational structure, interactions and the operational sequence timeline is not sufficient
to uniquely define the remaining two knowledge base data models;
functional allocation and objectives. Consequently candidate
functional allocations and objectives must be hypothesized and
tested against past historical patterns and future data collections. Automation will allow the analyst to handle more hypotheses than he could manually but certainly it still will not
be possible to exhaustively enumerate, store and test all feasible
hypotheses.
It will be necessary to choose and select only a
subset of the universe of feasible hypothesis candidaotes. The
heuristics associated with-the analysts expert knowledge base can
come into play here as rules, strategies or procedures for
selecting, pruning, and rejecting among the set of feasible hypotheses.
Based upon a given hypothesis many of the existing gaps in the data
models elements can be filled. Concurrently, known data models
elements can be filled. Concurrently, known data model elements
can be corsschecked for consistency and validity to rank and evaluate
the likelihood of a candidate hypothesis or to identify the possibility of purposely inserted false deceptive information by the
enemy.
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14. Example 3 is the most general and representative of the three
cases. In this example, all of the knowledge base data models are
understood partially, none completely. This case can be handled
through an adaption of the methodology just previously discussed for
example 2. The recommended steps are illustrated in this viewgraph.
General interactions of this procedure for a given set of
collected data may prove useful.
61
15. This viewgraph provides the caution that the collected
data used to develop and refine our knowledge base is noisy,
incomplete and random. Not only are the input and output
observations fundamentally noisy, but false signals may be
injected into the process. Further, one should be reminded
that the decision model used as part of our knowledge bases
hypothesis is based upon an assumed normative process. The
outputs observed are the results of an actual instance of a
specific real life decision maker. Accordingly, a hypothesized
decision model must by its nature be somewhat fuzzy. The
actual decision process will be somewhat unpredictable due to
the individuality of the decision maker involved. Further, as
discussed earlier, the decision maker may choose to work with
acceptable ranges or values of the parameter and-not with specific
values. In this case, the actual rules and optimizing strategy
themselves are inherently fuzzy. This suggests that the processing and matching of collected data to the hypothesized
knowledge base and the subsequent updating and verification
of this knowledge base is best approached through statistical
means; e.g., statistical confidences, estimations, and clustering
analyses.
63
16. In summary, it is felt that there is a systematic methodology
underlying the intelligence analyst process. That the explicit
delineation of that process identifies a set of tools for the analysts
that will assist him in a most fundamental way allowing for significant advances in both his productivity and in the quality of
his output. And, that these tools may be represented by the
areas indicated in the viewgraph: Candidate hypothesis optimization
models and techniques that relate the knowledge base data models;
Storage maintenance and representation of the multiple hypotheses
data models; Candidate hypothesis selection heuristics; Candidate
hypothesis search and pruning aids; Statistical estimation,
clustering and pattern matching aids.
65
DERIVATION
SYSTEM
(C
OF AN
/MIS)
A MARINE
INFORMATION PROCESSING
ARCHITECTURAL MODEL
CORPS
PERSPECTIVE
BY
Lieutenant Colonel James V. Bronson
United Stated Marine Corps
Code 033
MCLNO
Naval Ocean Systems Center
San Diego, California 92Z52
67
INTRODUCTION
This paper proposes a generalized command support system (CSS) reference
architecture for military information processing systems.
The proposed
architecture is derived for the most part in the paper from basic definitions.
U. S. Marine Corps and Joint Chiefs of Staff (JCS) documents are used as
sources and examples because of the background of the author.
Other service
publications could be applied instead. The underlying premise is that there
is an abundance of documented structure for describing the process of command
and its support.
The difficulty is in establishing the availability of the
resources and translating them into hardware/software entities.
A reference architecture has multiple uses.
First of all, at a concep-
tual level, it would describe the totality of information processing needs or as close to it as we can achieve. This becomes especially important as the
command, control and communications systems (C3) and management information
systems (MIS) come together in terms of requirements for timeliness and
information content. C3 systems have dealt with weapons direction and
perishable information. MIS were batch processed, - not so time critical and
seldom interactive. Force status, for example, usually determined by logistics considerations stated in the MIS becomes critical for the planning
functions of the C3 system.
A reference architecture has utility as a management tool. As systems
are specified, managers require a vehicle for displaying the bounds of their
charters, responsibility, and authority. Likewise, there is a need for a
reference in assigning tasks to subordinates and describing interfaces. A
good example is the need to state the responsibility for budgeting to meet
particular interfaces. In summary, the reference architecture provides a
method for audit to insure that all costs are recognized in considering the
process of command. At least, inclusions and omissions will be intentional.
A reference architecture has utility for training. It provides an
aggregate view of the information and processing facilities which a commander
must have. It provides a means for describing the scope of the information
used by the commander to potential commanders. Likewise, non-military
managers building military systems must occasionally be educated in the
process of military command. Their management of resource allocation might
well benefit from a managerial structure paralleling command organization and
partitions. Engineering staff working on military systems should be trained
or educated in the process of command. The messages the systems process and
the processing algorithms derive from the process of command, so a good
background will be most helpful.
A reference architecture will support system specification and engineering. It facilitates bounding the hardware/software assemblage. Relationships to other systems are obvious at any level of detail required. Processing within the system can be related to the functions of command.
This paper attempts to differ from many others on C3 in that it takes the
acknowledged defintions such as "command" and "staff" and uses them as the
basis further processing of the CSS problem. Command is treated as the
68
process of managing the production of armed force as a commodity. The
management is a flow through the steps of planning, organization, coordinating, directing and controlling. These are common processes. Particular
emphasis is given to definitions which avoid the use of the word being defined
in the supporting definitions, some of which will be used as examples.
An information processing system model is used to more completely depict
the command processes and its workload.
Staff functions are developed as the military technique for a work
breakdown structure so that the workload can be assigned to multiple workers.
Around the clock functional continuity is provided by centers in those areas
for which standard processes can be defined. Centrals are introduced as
hardware/software aids in the centers.
Finally, the layered architecture is
presented as a basis for describing specific interfaces to be addressed in
creations of centrals.
These seven building blocks are used in creating the reference architecture, sometimes called a model for simplicity. These are in a list format.
1i. The commander and command
2.
Processes of command
3.
An Information Processing System Model
4.
The Staff and Its Functions
5.
Operating Centers
6.
Centrals
7.
Inputs and Outputs
In summary, the commander's processes are used by staff functional
sections which are required to perform the volume of work. These staff
sections in turn create centers for continuity of operations. Centrals are
acquired to support accuracy, timeliness and cognition of information.
Interface definition is required to insure that the staff sections, centers,
centrals perform adequately in parallel and serial processes.
An example uses the derived reference architecture as the basis for
describing and comparing some aspects of the Tactical Flag Command Center
(Navy) and the Combat Operations Center/Tactical Air Command Center (Marine
Corps).
Conclusions finish the paper.
THE DERIVATION
Since we are dealing with a reference architecture, what is an architecture?
69
An architecture is the specification of the relationships between the
This
The introduction called out the major elements.
parts of a system.
section will attempt to deal with the details.
Building Block I - The Commander and Command
The first building block is the concept of the commander and command.
The following descripCommand rests in an individual who is the commander.
tion is extracted from Fleet Marine Force Manual (FMFM) 3-1 - Command and
Staff Action. 2
COMMANDER
"The commander alone is responsible for everything that his unit
He
does or fails to do and must be given commensurate authority.
cannot delegate his responsibility, or any part of it, although he
In discharging his responmay delegate portions of his authority.
sibility, the commander issues orders to subordinate units through
the chain of command which descends directly from him to his
immediate subordinate commanders, whom he holds responsible for
The commander issues
everything that their units do or fail to do.
orders and instructions to his staff through staff channels."
This description clearly describes a need for a "hands-on" manager.
The Dictionary of Military and Associated Terms, JCS Pub 1, provides a
The entire
more managerial text in the first of the four sub-paragraphs.
definition is provided for completeness.
"COMMAND - (DOD, IADB) 1. The authority which a commander in
the military service lawfully exercises over his subordinates by
virtue of rank or assignment. Command includes the authority and
responsibility for effectively using available resources and for
planning the employment of, organizing, directing, coordinating and
controlling military forces for the accomplishment of assigned
It also includes responsibility for health, welfare,
missions.
morale, and discipline of assigned personnel.
2. An order given by a commander; that is, the will of the
commander expressed for the purpose of bringing about a particular
action.
3. A unit or units, an organization, or an area under the
command of one individual.
To dominate by a field of weapon or fire or by
4.
See also AIR COMMAND; AREA
observation from a superior position.
COMMAND; BASE COMMAND."
(Author's underlining)
70
Note that two of the four definitions are particularly germane to an
architectural presentation.
Definition 1 specifies responsibility and
authority.
It further addresses managerial concepts of planning, organizing,
coordinating, controlling and directing. No additional amplification or
definition of these concepts is provided anywhere in the dictionary. This
deficiency must be addressed in this paper.
"Employment of" encompasses the
entire military art and science and is too aggregate to afford guidance. It
is the object of the other five processes. Definition 3 talks to units:
Units have capabilities as described in their Table of Organization and Table
of Equipment (T/O and T/E) to create armed force. The T/O provides rank and
skills of personnel required to accomplish the unit mission. The T/E provides
the hardware to accomplish the unit mission. T/O skills are related specifically to T/E hardware.
Several definitions associated with command are presented here to flesh
out the picture. Comments are provided as to the utility of these definitions
in creating a collectively exhaustive and mutually exclusive reference
architecture.
"CONTROL - (DOD, NATO, CENTO, IADB)
1. Authority which may be
less than full command exercised by a commander over part of the
activities of subordinate or other organizations.
2.
In mapping, charting and photogrammetry, a collective term
for a system of marks or objects on the earth or on a map or a
photograph, whose positions or elevations or both, have been or will
be determined.
(DOD, IADB)
3.
Physical or psychological pressures exerted with the intent
to assure that an agent or group will respond as directed.
4.
An indicator governing the distribution and use of
documents, information, or material. Such indicators are the
subject of intelligence community agreement and are specifically
defined in appropriate regulations. See also administrative
control; operational command."
Commentary on Control. Control is interesting because the cited definition (part 1) described in JCS Pub. 1 is a subset of command. Paragraphs 2, 3
and 4 are not relevant to this paper. Note that a senior headquarters can
assign the control authority to direct a unit to another of its subordinates
at any intermediate level. Hence we use the term command and control to
denote that in the organizational sense, the JCS Pub. I attributes are met and
likewise the unit or capability in question has not been meted out to another
headquarters for direction. However, it can be argued that the JCS Pub. 1 use
of control in the definition of command is more related to providing armed
force in accordance with the plan or directive.
Another view of control might state that the limiting factor is at the
staff agency. For example, control functions related to maneuver are delegated to the Operations Staff and not to other staff sections.
71
"COMMAND AND CONTROL - (DOD IADB)
The exercise of authority and
direction by a properly designated commander over assigned forces in
the accomplishment of his mission. Command and control functions
are performed through an arrangement of personnel, equipment, communications, facilities, and procedures which are employed by a
commander in planning, directing, coordinating, and controlling
forces and operations in the accomplishment of his mission."
Commentary on Command and Control.
This definition of command and
control uses four of the five functions of command (omitting organizing).
Note that "Direction" is used as synonymous with control.
"Control" is used
in both the item to be defined and the definition.
"COMMAND AND CONTROL SYSTEM - (DOD IADB) The facilities,
equipment, communications, procedures and personnel essential to a
commander for planning, directing and controlling operations of
assigned forces pursuant to the missions assigned."
Commentary on Command and Control System. The concept portrayed herein
does not address the command functions of organizing and coordinating.
Additionally, "control" again appears on both sides of the definition equation.
Building Block 2 - The Commander's Processes
Further definition of the managerial processes (responsibilities) is
essential to development of an architectural concept. These are derived from
The Theory and Management of Systems, by Johnson, Kast and Rosenzweig.
Plan is a predetermined course of action.
It:
Involves the future
Involves action
Has an element of personal organizational identification or causation.
Organize means to array material, energy and information to support
achievement of organizational goals.
(Every human is a source of energy and
information processing.)
Direct means to mobilize the flows of resources (material, energy and
information) to achieve organizational objectives.
Coordinate means to orchestrate the direction of resource flow to
maximize the effect, but with cost considerations.
It requires optimal
resource selection, schedule integration and conflict avoidance. The object
is to achieve mission objectives with least resource consumption.
72
Control is defined here as a system element containing a plan to achieve
an objective.
The elements consist of a controlled characteristic or condition, comparison of the state of the characteristic with the projected state
in the plan, and a mechanism capable of the required corrections.
The fine distinction between control and coordination can be demonstrated
by the idea that coordination involves only friendly forces without a directive relationship at that echelon. Control, on the other hand, must account
for and adjust to the entire environmental condition or state. It is based on
the comparison of measured characteristic state with predicted state.
Commentary on Control. It should be noted here that the common interpretations of the terms "control" and "authority to direct" are virtually
synonymous, hence have little utility as the basis for decomposing and
examining the architectural definition problem.
TRANSFORM
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Hereafter, control includes considerations of information exchange capabilities, and the plan. It is a closed loop system. "Direct" or "Direction"
means authority to order and the process of doing so; i.e., an open loop
system, and one way in the time interval of interest.
The military application of control concepts will bear further amplification. In the tactical sense, control has two subsets. The first is a
straightforward comparison of resource commitment (direction) to the projected
time line of the plan (schedule). Examples of these are troop maneuver or
preplanned fires.
The alternative to this is a review of the validity of the
plan in light of the current situation. Execution of the order may be
retarded by intense environmental action, natural or hostile. Flows or
resources have to be adjusted, e.g., on-call fires or counter-attacks. On the
other hand, if objectives are achieved at rates greater than initial assumptions would support, overall plan and schedule adjustments are required to
seize opportunities.
Thus, the dynamics of military operations require
constant cycling of all five command functions to maintain equilibrium with
the environment in the operating area. Likewise tactical control, in the
systems sense, is the most challenging aspect of the command function. This
latter concept of control becomes particularly important in the light of the
idea that the armed forces of the hostile are likewise attempting to achieve
73
their national objectives by eliminating or neutralizing the capabilities of
our side.
It is apparent that feedback loops are a critical aspect of the control
exercised by the commander.
It does him or the nation little good to exercise
absolute "direction" or open loop control if he is "out-generaled" and his
armed forces are destroyed.
In this context, he is constantly sensing his
environment to determine whether progress is according to his plan. The
commander's corrective mechanisms are applied once he determines that progress
has varied out of planned tolerances. These include priority for supporting
fires, committing the reserve, or presence of the commander, or he can change
the plan to be more consistent with current perception of environment.
These feedback loops are the most valuable part of the C3 system. If the
telecommunications capability is very good, i.e., reliable, adequate capability, secure, planning need not be so thorough and command can respond to a
highly fluid situation.
On the other extreme, inadequate telecommuncations
require intensive prior planning and the ability to describe options and
alternatives with minimum information exchange, i.e., red smoke or a yellow
star cluster.
Mission type orders such as the Civil War directive, "Move to
the sound of the shooting," become most important. Trust in subordinates
becomes critical and failure at a subordinate echelon can be crucial since the
senior headquarters does not have essential timely information on which to
base exploitation, reinforcement or counterattack.
These polarized situations dictated by the communications capability have
been characterized as open loop or closed loop.
The real world will be some
hybrid of the two. The viability of the telecommunications system is perhaps
the most crucial assumption of the C3 system design process.
Interim Recapitulation
A concept for an architectural model has been stated. Additionally, the
processes of command have been presented with emphasis on the individual
responsibility and his management in the process of executing the responsibility. Control has been heavily emphasized.
Building Block 3 - An Information Processing System
The next building block is the model of an information processing system.
A model is essential to considering the actions described in the definition as
a process.
The most generic type of this is simply input-process-output.
A
more tailored model has been proposed by Dr. Thomas Rona in a paper presented
at the Second C3 Symposium sponsored by the Navy at Monterey in July 1979.5
An extract from his paper follows as the description of the IPS model for this
paper. Note that links to the stimulus and effector sets are usually included
(telecommunications).
This model was selected because it separates the transform operator from the transform logic. The capability of the operator limits
the overall result of the logic.
74
"GENERAL
The command and control system is seen basically as a logical
mechanism to transform a stimulus set into an effect set. The main
components of the model are (1) the stimulus set, together with the
associated references;
(2) the transform operator; (3) the effect
set; and (4) the transform logic that prescribes the action of the
transform operator.
The model also comprises the stimulus and
effector links that tie these elements together but do not themselves introduce significant logical transformations into the
process.
In this formulation, all the information that is legitimately (i.e., according to the intent of the system designer)
brought directly or indirectly to the attention of the commander*
enters via the stimulus route. All the C3 system effects chosen by
the commander exit via the effect or effector route.
For the sake of completeness, and relevance to C3/MIS, we should
keep in mind that the transform logic must be connected with the
mission objectives, which comprise combat objectives of weapon
systems supported by the C3 system, and also with the combat
objectives, if any, directly associated with the C3 system and its
connected interfaces."
(See Figure 1)
This model can be modified with specifics, again referring to available
procedure. The format for an operation plan/order is cited. FMFM 3-1 calls
for major paragraphs (sections) for Situation, Mission, Execution, Administration and Logistics, and Command and Signal. The Situation paragraph describes
the friendly and enemy situation, including intelligence, as seen by the
issuing authority. The Mission is the tasking to the commander by the issuing
authority. Execution states the commander's concept and tasks his subordinates. Administration and Logistics (A&L) includes personnel and support
considerations.
Command and Signal (C&S) establishes key relationships and
establishes processes for communications. The Commander must accept and apply
the four paragraphs about which he can do nothing, (i.e., Situation, Mission,
A&L and C&S) process them, and create direction which is conveyed in the
following situation, execution, and amplified A&L and C&S paragraphs.
The transform logic the commander applies is described in his managerial
functions of planning, organizing, coordinating, directing, and controlling
(POCDC). The transform logic likewise applies technical considerations such
as weapons pointing calculations or aircraft corridor coordinates (commodity
unique).
(See Figure 2)
*Unless otherwise specified, this term refers to the individual responsible
for the C3 system operation.
75
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The commander, knowing that he has responsibility and a prescribed set of
managerial processes, then creates appropriate responses to either subordinate
commands or available weapons systems.
Building Block 4 - The Staff
Thus far, the commander has been presented as managing his war by
himself.
The 24-hour-a-day tempo and massive information flow associated with
war require support. The military provides this in the form of a staff.
A brief description of the staff is presented here; extracted from FMFM
3-1.
"GENERAL. - - The staff of a unit consists of those officers who
assist and advise the commander. Functions common to all staff
officers include providing information and advice, making estimates,
making recommendations, preparing plans and orders, advising other
staffs and subordinate commands of the commander's plans and
policies, and supervising the execution of plans and orders. The
commander and his staff should be considered as a single entity.
However, no staff officer has any authority in his capacity as a
staff officer over any subordinate unit of the command.
"STAFF ORGANIZATION
(1) Executive or General
which the commander is required to
command are grouped into six broad
the organization of the general or
are:
Staff. - - The manifold duties
perform in the exercise of
functional areas as a basis for
executive staff. These areas
77
(a)
(b)
(c)
(d)
(e)
(f)
Personnel
Intelligence
Operations and training
Logistics
Civil affairs (when authorized)
Financial Management"
The following diagram displays the concept of the model being applied
across five* functional areas created by the staff organization. The commander begins to spread the work load to accommodate the level of detail and a
natural breakdown of the information to be processed.
Each staff section
applies the POCDC transform logic to its functional area on behalf of the
commander. The result of this application appears in annexes and appendices
to operational plans, orders and as Standing Operating Procedures.
(See
Figure 3.)
Building Block 5 - Centers
Over the years, military organizations have evolved the "center."
Centers are special in that they focus on a narrower span of activity but
handle it with as much detail as required. There is no lower level of
organizational addressal of an operational problem. Some centers have
representatives from several commands in process of coordinating their
activities.
Others operate on a 24-hour/day basis with a high level of
specialization. In nearly all cases, they perform routine tasks on information which can be specified in advance. This is not to say that the processes
are not life and death or critical.
In fact, the "dispatcher level" of work
of managing the production of armed force is performed in the centers.
As an example of the wide range of centers in use in military organizations, the following list has been extracted from FMFM 10-1, Communications. 6
Each of these can be mapped to the sponsorship of a particular staff agency.
Each can apply the IPS model as a describer of its processes.
The transform
logic of POCDC applies, focused on short term operations. The type of information processes is identified to a large degree by the names of functional
radio nets entered by a particular center.
It should be noted that there are no centers associated with tactical
personnel operations. This does not preclude establishment of one, if
circumstances require. Additionally, the overwhelming number of these centers
are associated with operations.
They are not all located at all echelons, but
are associated with maneuver, supporting arms, aviation, logistics and
communications. A structure (architectural model) displaying the coherent
array of all centers is helpful.
*Civil Affairs is deleted in view of its "as authorized" nature.
78
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(from FMFM 10-1)
STAFF SECTION
a.
b.
Landing Force Control Agencies
(1) Combat Operations Center (COC)
Operations
(2) Fire Support Coordination Center (FSCC)
Operations
(3) Fire Direction Center (FDC)
Operations
(4) Tactical Air Command Center (TACC)
Operations
(5) Tactical Air Direction Center (TADC)
Operations
(6) Tactical Air Operations Center (TAOC)
Operations
(7) AntiAircraft Operation Center (AAOC)
Operations
(8) Battery Control Center (BCC)
Operations
(9) Direct Air Support Center (DASC)
Operations
(10) Logistics Support Coordination Center (LSCC)
Logistics
(11) Signal Intelligence/Electronic Warfare
Coordination Center
Intelligence
(12) Tactical Surveillance Center (TSC)
Intelligence
Amphibious Control Agencies
(1) Supporting Arms Coordination Center (SACC)
Operations
(2) Tactical Air Control Center (Afloat)
(TACC (Afloat))
Operations
(3) Force AntiAir Warfare Center (FAAWC)
Operations
(4) Helicopter Direction Center
Operations
(5) Tactical-Logistical Control Group (TAC-LOG)
Operations/Logistics
(6) Helicopter Logistics Support Center (HLSC)
Logistics
(7) Navy Control Organization
Operations
80
CENTERS (from FMFM 10-1)
(Continued)
STAFF SECTION
c.
Communications Control Agencies
(1)
Operations
Communications Control (COMMCON)
(a)
System Control (SYSCOM)
Operations
(b)
Technical Control (TECHCON)
Operations
(c)
Communication Center (COMMCEN)
Operations
(d)
Switching Center (SWECEN)
Operations
(e)
Special Security Communication Center
Intel
(SSCOMMCEN)
To this point, the concept of information processing for command support
has become more and more structured. The commander applies an IPS model to
his processes, a staff is established for work distribution functional
specialization, but using command processes, then centers are established to
support around-the-clock operations on particular types of information. At no
point has the necessity for automation been established. The work can be
accomplished manually and has been traditionally (See Figure 4.)
Building Block 6 - The Central
The computer supported center will change the process of command substantially. A central is the collection of facilities (hardware and software)
necessary to support a center. The computer operates on binary states, hence
everything which has been happily handled (albeit loosely) by the human senses
and intellect now has to be converted to a stream of ones and zeroes, the
processing of which must be very explicitly and precisely defined.
In the IPS model, the stimulus set takes the form of digital messages
representing the situation mission, A&L or C&S, or environment. These may be
received over telecommunications lines or operator input. The transform
operator is a digital computer, the transform logic is in the computer
program. The effector set may be a digital stream to another system or hard
copy for human use.
The central operates exclusive of the communication
system, except for system control message exchange. This relates to level 4
through 7 of the reference model described as Building Block 7.
It is safe to say that no central will be able to meet all military
information processing needs. However, the high degree of assistance provided
will allow the humans in the center to focus on the aspects they handle best,
i.e., poorly defined.
81
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Building Block 7 - The Inputs and Outputs
The last major building block for a generalized architecture is the Draft
International Standards Organization (ISO) Reference Model of Open Systems
Interconnection.
"Open Systems Interconnection refers to standards for the exchange of
information among terminal devices, computers, people, networks, processes,
etc., that are 'open' to one another for this purpose by virtue of their
mutual use of the applicable standards."
This concept is important to an
architecture because it allows expansion in a controlled manner. The interfaces of any number of system elements can be described. This is a sevenlayered protocol which is summarized as follows:
o
Level 1, physical control, concerns the actual means of bit transmission across a physical medium.
o
Level 2, link control, enables logical sequences of messages to be
exchanged reliably across a single physical data link.
o
Level 3, network control, provides logical channels capable of
reliably transferring information between two endpoints in a single
communication network.
o
Level 4, transport end-to-end control, provides reliable endpoint-toendpoint transport of messages across an arbitrary topological
configuration through several interconnected networks.
These lower levels are collectively referred to as the transport service,
and the Level 4 interface (between the fourth and fifth layer) is called the
transport service interface.
It represents a well defined interface that may
be established between a communications carrier (provider of transport
service) and a data processor (user of transport service).
o
Level 5, session control, provides sessions or high-level connections
supporting the dialog between pairs of workstation processes.
o
Level 6, presentation control, provides required format transformations of information being transferred.
o
Level 7, application, is the level of the work station process
itself.
This reference model is critical to adequately describing the relationships
between elements in the CSS. Examples of these might be data entry devices,
data communications equipments and computers themselves. It is likewise of
use in describing non-automated systems; a new system user has an initial idea
of where to look for particular types of information.
This model establishes the reference for describing in detail the stimuli
(Situation, Mission, Environment, A&L and C&S) and effector (Execution).
83
Through its use, CSS can be built for various echelons of command and various
commodities such as aviation, maneuver, or artillery. The transform logic
will be dependent on the command being supported in terms of the specifics of
operations on particular data fields.
Interoperability can be traced to a
particular reference level and function being supported.
The thread of this paper has begun with the commander who is responsible
for the achievements of his unit. Management of the processes of application
of armed force goes through the processes of planning, organizing, coordinating, directing and controlling.
A conceptual model of the information
processing system to support command is presented. The model uses the command
management process of planning, etc., together with commodity algorithms as
the basis of its transform logic.
These later are shaped by the commodity
being managed, i.e., manpower, fire support, aviation, logistics, communications. The commander creates a staff to manage functional areas and break
down the workload.
Each staff section applies the model to its processes for
a particular area.
Staff sections sponsor centers for around-the-clock
operations in specified operational areas.
They perform planning, organizing,
coordinating, directing and controlling for the command on more structured
inputs over a narrower time interval for response and planning.
This continuous sharpening of focus on detail leads to the central which operates on
digital formats, using a computer for the transform operator and a computer
program to describe and convey the transform logic. The structure for
describing relationships of centrals is described via an ISO Standard for Open
System Interconnection.
It should be noted that this architectural model is independent of
hierarchical position and commodity area.
It focuses on the commander, his
functions, and the information necessary to support them.
It is infinitely
expandable by adding slices and addressing the points of interoperability.
An Example
A recent opportunity to demonstrate the use of a reference architecture
occurred during an exchange of ideas between Navy and Marine Corps members on
the subject of the Tactical Flag Command Center (TFCC). Nominally, the Marine
Corps interface to the TFCC would be accommodated by the Combat Operations
Center (COC) or Tactical Air Command Center (TACC) located at the Commander
Landing Force (CLF) Headquarters.
The discussion revolved around the potential interoperability of these Navy and Marine Corps centers.
The reference architecture provided the basis for the individual being
briefed to rapidly assimilate and evaluate systems in question. Required
elements of the C3 system are known in advance.
The issue then becomes how
the systems being described relate to the reference as a basis for comparing
the TFCC and COC/TACC.
The next few paragraphs provide a thumbnail sketch of the TFCC and
COC/TACC.
Summary information only is provided since the purpose of the
presentation is an example of a generic architecture being used as the basis
of system comparison.
Using an unclassified article from Surface Warfare
84
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"Tactical Flag Command Center" as a simplified source, the
January 1981
following TFCC capabilities are listed:
o
Special intelligence presentation
o
Navy Tactical Data System presentation
o
Dead Reckoning Trace
o
Access to ship communications and display capabilities such as
telephone, television and radio through a central console
o
Manual back-up
The second phase of the TFCC program will be a central derived from the
AN/USQ-81 designated the Flag Data Display System (FDDS). Capabilities of the
FDDS will include:
o
All source integrated tactical situation display of air, surface and
sub-surface data
o
Display overlays (to enhance cognition)
o
Detailed track information
o
Technical characteristics data base
o
Staff Planning and data manipulation aids
The COC is currently a manual capability using overlaid maps, status
The TACC has a
boards, and supported by voice and teletype communications.
computer supported display capability for real time display of aircraft tracks
It is NTDS compatible.
The planning function is manually
and status.
supported with access to voice and teletype communications.
The COC/TACC will be upgraded with the addition of the Tactical Combat
Operations (TCO) System in the post-1985 timeframe. TCO will use the hardware
suite being built for the Marine Integrated Fire and Air Support System
(MIFASS). The hardware/software assembly (central) will support:
o
Planning
o
Intelligence processing
o
Real time situation display
o
NTDS interface (via the Tactical Data Communications System)
o
Message Processing
o
Data Base management
86
o
Mission Statement Processing
The first face of the architecture is command processes. The inputs on
which both centers focus in the situation through intelligence displays and
friendly status. These are operational centers and do not seem to focus on
Administration and Logistics (A&L) and Command and Signal (C&S).
The use of a
generic architecture raises the question of the adequacy of addressing these
issues. This applies particularly to Command Relationships.
Command relationship confusion impacted the attempt to rescue the hostages in Iran.9
Using the architecture, the transform operators can be anticipated and
described. The current TFCC, COC and TACC capabilities have limited computer
support, primarily through NTDS based systems, including those USMC capabilities compatible with NTDS.
Future capabilities will include the AN/USQ-81(V)
for the Navy and the TCO system of the Marines built around hardware developed
for the Marine Integrated Fire and Air Support System (MIFASS). Both are
being procured with an eye toward supportable densities within the service.
Transform logic is classified as Planning, Organizing, Coordinating,
Directing and Controlling and Commodity Unique. The TFCC description does not
address these functions discretely. Inspection of the previously provided
list establishes that TFCC addresses features of the display capability.
Planning aid is described as a capability of the FDDS. There is no requirement to address these functions explicitly. However, since the functions of
command are stated in JCS Pub. 1, it would be nice if they were used as the
basis for describing command system features.
10
Similarly, the TCO system is described in the MTACCS Master Plan
as
supporting planning, directing and monitoring operational and intelligence
information. Again, the processes spelled out by the definition of command
are not addressed explicitly.
The TFCC description does not address system output requirements execution or mission statements to subordinates, A&L and C&S.
(NOTE: These
are probably covered adequately in system documentation but not explicitly
presented in the write-up.)
The summary TCO description does address the need
to issue directives, but omits A&L and C&S. Again, in review of a system, an
a priori reference architecture can properly serve to raise the question of
how critical areas are implemented.
Turning to the top face of the prism which the reference model resembles,
we see the staff functions in terms of the 1, 2, 3, 4 of the General Staff.
The TFCC does not incorporate this construction of personnel, intelligence,
operations and logistics functions.
If the structure of the model were
applied, TFCC would address many of the intelligence and operations functions
(G-2/G-3). The definition of the relationship of the TFCC to the Composite
Warfare Commander functions would be helpful. A highly integrated (G-2/G-3)
statement could be anticipated.
COC/TACC functions can be mapped more directly to the intelligence and
operations sections since the Marines use a General Staff organization.
87
However, looking at either TFCC or COC/TACC now concentrated in the
G-2/G-3 elements of the architecture, it is reasonable to examine them more
specifically for treatment of input-process-output.
Status information is
processed as input for planning, coordinating and directing (From describing
documents).
These are the results of messages specified in the operations
order. There are several sets of formats such as rainform or JOPS.
The exact processing associated with planning, organizing, coordinating, directing and controlling is not clearly defined. This gap is
covered in the unique processes of staff personnel.
Finally, the expected
outputs are identifiable and can be related to Execution assignment, A&L and
C&S, in general operation order format.
The question the architecture raises for both the Navy and Marine Corps
is the concept of control as a closed loop process. Implicit in the descriptions are control loop processes but the lack of explicit addressal in this
context is bothersome.
Within the construction of the staff, it is feasible to demonstrate TFCC
and COC/TACC as operating at the center level.
Information used and functions
performed are routinized and highly structured. (However, the names give this
away in advance.)
The AN/TSQ-81(V) and TCO system are likewise identifiable
as the centrals, which are hardware and software having a physical measurable
identity.
Use of a generic C3 architecture has provided a reference for looking at
two specific capabilities in an organized manner. Both have been shown to be
strong in situation display, focused on the stimulus-response but without an
underlying control loop theory.
Finally, the third dimension of our system level discussion of TFCC and
COC/TACC can be addressed in terms of the Draft ISO Reference Model for Open
Systems Interconnection. Both centers cross all seven reference model layers.
TFCC at the physical control level terminates voice circuits as does the
COC/TACC.
Computers and peripherals are cable linked with cable termination
pins identified and described by military standard interfaces. Link control
addresses COMSEC among other attributes such as ringing schemes.
There will
be some voice compatibility between Navy and Marine systems. However, because
of a Navy orientation to 2400 bps/3 kHz circuits, and Marine use of 16 kbs/25
kHz circuits, these will be at a minimum. Network control is the point at
which some more incompatibilities emerge. TCO is oriented to being serviced
by a multi-channel switched system. It will have some NTDS interoperability
via the TACS/TADS JINTACCS programs.
FDDS has a narrow band satellite focus.
Transport end-to-end control can be manually addressed via DCA protocols.
However, on-line interfaces are incompatible as at the level of communications
to computer interface.
TFCC is bounded by the Navy 2400 bps architecture.
TCO is focused on the TRI TAC 16 kbs architecture. It is not designed for
full period narrowband satellite terminations. The reference architecture
allows rapid focusing on a potential incompatibility and its nature.
However, for demonstration purposes, the review of the ISO Standard will
be continued and applied to the TFCC and COC/TACC. The next level is that of
88
session control. Systems have to be interoperable in that each can decode,
process and output the messages exchanged with the other. It is at this point
that content and function become associated with the command process abstractions of input (situation, mission, environment, A&L and C&S) processes (plan, organize, coordinate, direct, control, commodity unique) - output
(execution, A&L and C&S).
Interoperability standards are now being written to support this requirement. TCO will use JINTACCS standards. To the degree that the AN/TSQ 81(V)
incorporates these standards, there could be interoperability on selected
links.
Session control also addresses the process of coordinating information
exchanges between work stations. My interpretation of this process: half
duplex or simplex. The system might be fully synchronous or interrogate/
respond. It seems that many of the packet data exchange network control
approaches such as aloha, star or ring could be attributed to this level,
since the frequency of information exchange would drive the session tempo. If
the exchange rate is high enough, however, the session control would be
dealing with a need for virtual total connectivity and this coordination
function would be more properly associated with transport end-to-end control.
Presentation control requires format transformations. This is the
processing interface between the user and session control. The operator
requires a human language syntax and adequate graphics. The computer system
prefers bit oriented messages and process for minimum storage and simplified
instruction handling. Hence, at this level, the human-to-binary interface
must be made.
Standardized transform codes are not frequently mentioned in the literature. Examples of this might be operators associated with plan or direct.
"Plan" might use operators related to time and place. "Direct" might use
operators related to word processing and other message handling functions. The
conditional tense is used here to emphasize the currently unstructured aspects
of programming language features related to abstract definitions. A compiler
syntax for these architectural abstractions would have value. Artificial
intelligence may be a solution.
The Application must support virtual transparency between users. In the
real world, this is accomplished by restricted menu and symbol sets and
training operators up to that standard. Both presentation control and the
application layer for TFCC and COC/TACC might have conceptual interoperability
on the basis of standard symbology and prompting menus. This coordination has
not been affected.
In summary, the reference architecture has been used as a basis for very
broad description discussion of two capabilities. Its use supported rapid
focus on similar functions, yet virtual incompatibility with specific exception.
89
CONCLUSIONS
The definition of command by itself provides the basis for a generic C3
architecture.
The remainder flows from the processes of command, functions of
the staff supporting a work breakdown structure and the standards for describing interfaces. On this basis, C3 systems should be designated command
support systems, since control is only one of five processes of command.
C3I
is likewise inappropriate, since intelligence is only one of five major staff
functions. Both observations are based on use of basic definitions.
Other basic definitions associated with command lead to confusion, since
they include the term being defined in the definition. A rework of the
Dictionary of Military and Associated Terms might be in order to insure a
clear understanding of its processes and functions. That which is being
controlled should be identified.
The military has an abundance of existing reference material describing
its processes.
This material should be adhered to more in defining centrals
for command support.
The reference model for open system interconnection is a useful and
viable tool for describing systems and their relationship to other systems.
An area which could use more work is definition of a language syntax associated with planning, organizing, coordinating, directing and controlling.
This may well be fundamental to implementation of interoperability at the
presentation control layer.
Input and output message forms are straightforward; the transform logic standards will be more difficult.
The example demonstrated that exposition and review of concepts and
systems is expedited and enhanced by knowledge of the subject matter beyond
that immediately being addressed.
The definition of command support systems
or C3 reference model is too critical to be left in the "too hard" basket.
SUMMARY
Just as knowledge of what an automobile looks like enhances a rapid grasp
of its features, we need a similar simple acceptable model of our command
system.
90
REFERENCES
1.
Cypser, R.J.
Communications Architecture for Distributed Systems,
Addison-Wesley Publishing Company 1978
2.
Fleet Marine Force Manual (FMFM) 3-1, Command and Staff Action P1
3.
JCS Pub 1, The Dictionary of Military and Associated Terms P. 85
4.
Johnson, Kast and Rosenzweig
PP 15-16
5.
Rona, Thomas
6.
Fleet Marine Force Manual (FMFM) 10-1, Communications
7.
American National Standards Institute
Interconnections 7498
8.
Surface Warfare, Tactical Flag Command Center January 1981 PP 8-9
9.
Aviation Week & Space Technology
Sept 15, 22, 29, 1980
10.
Marine Tactical Command and Control System Master Plan
PP 2-24
The Theory and Management of Systems
Generalized Countermeasure Concepts in C3I
1979
Section 3
Data Processing - Open Systems
Group Analyzes Reasons for Failure
91
24 Apr 1981
92
A
CONCEPTUAL CONTROL MODEL FOR DISCUSSING
DIRECTION SYSTEM
(C
) ARCHITECTURAL
BY
Timothy Kraft
Comptek Research Inc.
10731 Treena Street
Suite 200
San Diego, California 92131
and
Thomas Murphy
NAVSEA 61Yll
National Center Bdlg. 2
Washington, DC 20360
93
COMBAT
ISSUES
A CONCEPTUAL CONTROL MODEL FOR DISCUSSING
COMBAT DIRECTION SYSTEM (C2) ARCHITECTURAL ISSUES
Timothy Kraft
Comptek Research, Inc.
10731 Treena Street, Suite 200
San Diego, CA 92131
(714) 566-3831
Thomas Murphy
NAVSEA 61Yll
National Center Bldg. 2
Washington, DC 20360
Abstract
This paper presents a conceptual model of a ship's combat system developed
for the Advanced Combat Direction System program. It provides the fundamental
relationships of combat direction to command, control and communications and to
the sensor and weapon elements of the combat system important to top level CDS
architectural and design considerations.
The conceptual model goes beyond current Navy Command and Control design
which attempts to federate the CS into separate elements to present a layered
control model which satisfies a hierarchy of response requirements. This control
model is shown to be consistent with both the requirement for simultaneous and
independent multiwarfare control and the CNO NTDS Function Allocation Study.
The implications of this model upon combat direction system architecture are finally stated as they apply to the management and technical development of future
advanced combat systems.
Paper presented at the ONR Workshop on C3 , San Diego, CA, June 1981.
94
1.
Introduction
The increasing complexity of modern combat systems has widened the development gap between high-level requirements and the establishment of the operational
baseline of hardware and software components with supporting documentation. The
ship's combat direction system (CDS), which must interface with many of the combat
system and command, control, communications, and intelligence (C3 I) components,
reflects much of the complexity in evolving combat system design. (Section 2
describes the ACDS/C3 relationship further.) With complexity come expanded requirements for technical expertise and a concomitant increase in management bureaucracy to coordinate the many activities. Because Naval Tactical Data Systems
(NTDS) were the first shipboard computer systems and have evolved into the
primary component of shipboard command and control support, the NTDS community
is well aware of the technical and management problems associated with complex
systems ( 6).
One proposed solution has been to further partition the CDS into federated
components that can be developed and managed as separate elements (5). This, however, only partially addresses the issue of complexity. Any strict partitioning
without an overall systems approach would ultimately compromise the CDS's
ability to support Command because of the large number of interactions among
element managers that would be required to support the design of a CDS. Also,
due to the expanding scope of Command's concern, and the range of possible responses
to counter threats in highly complex and dynamic tactical environments, the responsibilities of Command can be expected to increase rather than diminish. If the
scope of authority is well defined and meets the contingencies of the current
tactical situation, the ship's command authority will delegate authority to lower
echelons in the ship's command hierarchy. The delegation of authority cannot
be dictated by system design; rather, for the reasons delineated above, CDS must
be responsive to Command over the entire spectrum of tactical contingencies and
support a flexible scheme for dispatching Command's responsibilities.
The ACDS systems engineering approach incorporates a top-down structured
methodology to provide decomposition of system complexity into simpler subsystem
components, and to incorporate a large number of objectives within a unified
system design. This approach places increased emphasis upon front-end analysis
with systems engineering to provide sound CDS designs, as well as to anticipate
and resolve issues early in the development process. To support this, a highly
formalized systems engineering approach, which includes personnel, hardware,
and software requirements as the integral parts of the CDS architecture, has been
defined. Planning within the ACDS Project is directed primarily toward advanced
development of combat direction systems. However, the planning does consider
CDS interaction relative to other major design elements of C3 I, sensors, and
weapon systems. Therefore, because the common interacting element is the CDS,
it is important to understand the pivotal role of CDS in combat system design and
interoperability before defining the CDS architecture. The CDS critical role in
combat system interoperability and design is demonstrated in Figure 1.
The following sections present a conceptual control model of a ship's combat
system which reflects current capabilities while anticipating advanced developments. A similar activity was directed by Chief of Naval Operations to investigate the appropriate allocation of combat system functions to NTDS (3). The
study group representing various Naval branches of engineering, material and
operations formulated a similar conceptual model. Both studies draw heavily upon
operational experience and anticipated technological trends to generalize a
95
generic structure of command and control systems. Furthermore, both approaches
combine both man and support systems in an integrated system definition of C3 .
The conceptual model presented here goes beyond the CNO function allocation
study to discuss how control is structured within a combat system. It addresses
the problems that arise in the delegation of authority within a distributed ship's
structure. Therefore the two models complement one another with CNO study allocating functions within the combat system, and the ACDS model defining the control
interactions within the combat system. Sections 2 and 3 describe the relationships of combat direction to C3 I and other combat system elements. Section 4
presents how the conceptual control model addresses the issue of delegation of
authority and the resulting command and control structure required to support
multiwarfare (AAW, ASW, ASUW) engagement. Section 5 summarizes the implications
of the model.
C31
\C OMBAT/
Figure 1.
CDS, One of the Four Major Elements of Navy Systems Design
96
2.
ACDS/C
3
Relationships
The C3 network is supported at various levels by intelligence gathering and
environmental support centers which provide operational command with the required
information to support mission planning. This entire network is referred to as
command, control, communications, and intelligence (C3 I). The CDS is the "effector"
node of the C3 network - directing the weapon and sensor assets of ownship, battle
group, and/or supporting battle force command and control. The relationship of
CDS to the Navy C° structure is illustrated in Figure 2. Figure 3 gives the relationship of the various command and control nodes and the inter/intra Battle
Force Combat Direction Networks.
KEY:
rt
COMMAND NET
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COMMAND CENTERS
(FCCs FOR CINCLANT
&CINCEUR)
NCCS
FLEET]
COMMAND
CENTER
(CINCPAC)
MBAT
TTYPICA
INFORMATION SHIP <CISi
fFORCES
TYPICAL INDIVIDUAL
COMBAT SYSTEM
(SHIP PLATFORM)
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WEAPONS
* COMMUNICATIONS
* OTHER SYSTEMS
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Figure 2. CDS Relationship to Navy C3
The CDS will perform the following roles within the C3 I network:
a. It will operate in conjunction with the Tactical Flag Command Center (TFCC)
and other CDSs as part of a distributed Battle Force Combat Direction System.
b. It will operate in conjunction with other CDSs either as a participating
unit or as a commanding unit of a multiunit battle group responsible for execution
of some aspect of the battle force mission.
c. It will direct the elements of its ownship combat system, including air
97
platforms in close control, to support the battle force in simultaneous and independent engagement within all warfare areas.
GLOBAL
COMMUNICATION
INTRA-SHIP
COMMUNICATIOC
system
N
-NT ;
(nottobecofusedwit a
n
r
F
S
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'NTER-CENTER
COMiUNICATIONS
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t-LEET
SFLEET
COMMUNICATIONrtS
TFCC
CDS
COMMUNICATIONS
INTER- BATTLE
BATTLE
~CDS
)FORCE
( A
CDS
CS
BATTLE
GOUP
CDS
Figure 3.
Inter/Intra-Comunmication Networks and Command and Control Nodes
The distinction between battle force and battle group is the degree to which
multiple units are coupled into one system. At the force and group level, no one
system (not to be confused with a human) is responsible for the entire combat
direction of the force or group. Instead, multiple systems distributed among the
participating units data linking with each other
the make up
battle force or group
CDS. These real-time systems are linked by Tactical Digital Link (TADIL) and
voice communication networks. The functions performed by the CDSs as part of the
Battle Force/Group Combat Direction System is illustrated in Figure 4. The TADIL
communication networks can be thought of as the "data bus" interconnecting the
CDS and TFCC as shown in Figure 5.
Within C3I, intelligence is gathered and plans are formulated and propagated
down the command hierarchy. At each level of planning, the plan is expanded until
a detailed engagement plan is formulated by all participating units. If, in the
execution of a mission plan, a great deal of interaction and coordination among
distributed systems will be required, then the group is to be considered closely
coupled. On the other hand, if portions of the battle force plan are delegated
to closely coupled battle groups whose only requirement is to provide timely
status reports concerning the execution of responsibilities, then the battle force
98
is said to be loosely coupled. The spectrum from a loosely coupled to a closely
coupled multiunit cdistributed system is dependent upon the information band width
and accessibility of the communications network. The deployment of JTIDS Phase II
and the development of TADIL J, which will exploit the information bandwidth and
access capabilities of JTIDS, will greatly expand the opportunities for closely
coupled multiunit responses and, in turn, increase the effectiveness of the battle
group. The CDS will be required to support the entire spectrum of multiunit responses, either as a participating unit or command unit supporting one or more force
commanders of the battle force management hierarchy (CWC concept).
BATTLE FORCE
THREAT IDENTIFICATION
WEAPONS ASSIGNMENT
AIR TACTICAL DATA
SYSTEM (ATOS)
AIR
-
b
ICONTROL
BATTLE FORCE
~SURVEILLANCE
-~~CO°A~~~~MPORF°RSIT~E
/
COMPOSITE
WARFARE
COMMANDER
SUPPO
s
r
OWNSHIP
COMMAND
SUPPORT
INTEGRATION
NTEGRATN
;:FBATTLE FORCE
TRACK MANAGEMENT
.Lz
·
~
ON SHIP
SENSORS
-
\
a
dc~i~-c?
<MULTIWARFARE
AREA
C
FORCE
COMBAT
Fgur
. COS
MULTI-UNIT
BATTLE GROUP
COORDINATION
_
W
oEAPONS
g r
teCDS
D
;
WARFARE
~/
<\
sad~~-~~~g-~~
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X
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E
a
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IT.1
Figure 4.
j
2
~
_m
- /3i12
SURVEILLANCE
INFORMATION
-EXCHANGE
CDS - The Key to Effective Intra-Battle Force Integration
Having a number of CDSs capable of flexible multiunit configuration greatly
enhances the capabilities of the Composite Warfare Commanders (CWC) and increases
the survivability of the battle force by permitting distribution of battle force
command authority to meet the contingencies of the tactical environment. The
elimination or disruption of any unit can be effectively countered by the reconfiguration of the remaining units.
99
The CDS capability to be responsive to the mid- and long-term C 3 I environment
consists of providing multiple levels of automation support commensurate with
crucial Command response time requirements. The long-range goal is to provide a
continually leading technology base of design concepts for CDS engineering developments. The systematic approach to CDS R&D will encourage optimal usage of combat
system resources for mission needs as opposed to the after-the-fact "crisis"
interfacing currently employed. In this manner, CDS development can be responsive
to constantly changing combat system requirements and can facilitate optimal system integration. Finally, it can protect the multibillion dollar investment in
deployed combat direction systems from technological and/or threat-imposed obsolescence.
COMMAND
COMMUNICATIONS
INTER BATTLE FORCE
COMMUNICATIONS
a
\
MTa
SUPPORT
CENTER
INFORMATION
TFCC
t
i
a
mj
SUPPORT
DIRECTION
SYS
(aR
SYSTEM
SE/OR
~VOICE AN
TAIL
SEN
SYSTEM
NFORMATION
8US
INFORMATION \
SUPPORT
]
CENTER
'i
\
INfORMATION
SUPPORT
\
CDS
WEAPON
SYSTEM
SENSOR
SYSTEM
CDS
S ST
SHIPS
COMBAT
Figure 5.
Battle Force (Group) Combat Direction System
ACDS is concerned with an approach to CDS design thaj allows the development
of a family of CDSs and facilitates the use of standard C building blocks (hardware and software). This emphasizes the need for an approach which permits continual and evolutionary shipboard CDS upgrades. It is necessary that the CDS simultaneously and individually support single and multiunit engagements in all major
mission areas supported by the (AAW, ASW, ASU, AMPH and Strike), with increased
emphasis upon offensive operations.
100
This is in contrast to the force and self-defense measures which stress anti-air
warfare (AAW); in particular, anti-ship missile defense (ASMD).
It is important that ACDS provide the Combat System Architect with a unified CDS
appraisal which includes all aspects of combat direction as part of the C I network.
3.
ACDS/Combat System Relationships
The ACDS will operate within a tiered combat system architecture. The layering of the combat system (CS) is the result of current technology-driven evolutionary trends, with many combat system functions being embedded in the various
subsystems. A new CDS architecture will be required to account for technological
advances in sensors, weapons, and communications which have greatly increased the
degree of automation within the combat system. The increased data processing load
and the growing complexity and sophistication of the expected threats and missions,
coupled with requirements for faster engagement responses, have necessitated
complete redefinition of the scope and function of the CDS.
The CDS architecture will be defined within the context of a conceptural control model of a combat system. The conceptual model must address the following
fundamental considerations:
a. What is the relationship of Command (CO/TAO) to the ship's total CS?
b. What is the function of a CDS and its relationship to the other elements
of the CS?
c. Are there technological constraints that define the form of ship's CS
independent of fiscal constraints?
The control model described herein presents the conceptual control structure
(vs. a functional structure provided by the CNO functional allocation study) of
a generic combat system. An actual system could be far more complicated; however,
the salient features of a combat system structure are summarized to provide an
overall framework for discussion of combat direction system architecture. The
major conceptual functional groups of the combat system are:
$
Multisource Surveillance Function (MSSF) consisting of all functions within
the CS that support the search, detection, and identification of targets
in the tactical environment, including sensors and information sources.
*
Multiwarfare Engagement Function (MWEF) consisting of all functions within
the CS that directly control engagement of targets within the tactical
environment, including deployment of weapons platforms and hard and soft
weapons.
*Multiunit Command and Control Function (MUC2F) consisting of all functions
within the CS that support the planning, assessment, coordination, and
control of the combat system resources, including communications among
multiple units and propagation of information throughout the system or network.
These functional groups do not partition the operational functions of a combat
system. In fact, there is a great deal of overlap, with many functions being cate101
gorized within two or three elements. It is this ambiguity in allocating functions
that makes these functional groups inappropriate as submodels of the combat system.
However, they do reflect the basic sensor/director/effector cybernetic pattern
which is found duplicated on minor and major scales throughout the combat system
architecture. The combat system is characterized by a complex data processing and
control network with a layering of functions. Control is distributed throughout
the system rather than being exercised by one control director. The objectives of
tiered distributed control and, in turn, the integration of sensor/director/effector
include (4):
*
The reduction of information bandwidth as information propagates away from
the sensor, reducing measurement error and compacting information content.
*
The reduction of the response time for the engagement function, once a
stimulus has been received by the surveillance function.
The layering of the response within a combat system can be characterized by
the following:
0. Reflexive response: The reaction is immediate, based upon wide bandwidth
(or immediate) information.
1. Considered response: The reaction is protracted in time, requiring a
coordinated set of actions to achieve an objective.
2. Creative response: The capability to create and assess plans, initiate
and change tactics, improvise, and adapt to unexpected contingencies.
3. Coordinated multiunit response: The capability of multiple independent
units to organize and coordinate their responses to achieve a battle group
(closely coupled) or battle force (loosely coupled) objective.
In the "reflexive" mode, the response is based upon immediate data with little
predictive capacity. The "considered response" requires a more correlated picture
to be able to predict actions over the period of time of the response. The "creative
response" requires the correlated picture, the identification of relations within
that picture, and the stability to be able to assess plans and objectives over a
long period of time. The "coordinated multiunit response" requires a tactical
picture of the area of concern for the battle group or battle force, and a predictive capacity which supports plans that extend hours or days into the future. The
results from this layering of response is a parallel tiering of data processing to
support the information content requirements of each level. The tiers are:
0. Tier 0 processing: Processes the initial signal to form a contact that is
valid for only the time of measurement.
1. Tier 1 processin : Correlates contacts from one or more sensors to form
tracks representing a correlated set of data.
2. Tier 2 processing: Forms the tactical picture from Tier 1 tracks and
other external Tier 2 sources to represent the platforms and the interrelationships among platforms in the tactical environment.
3. External Tier 2 processing: The collating and management of information
distributed among multiple unit data bases so that a consistent battle
force/battle group wide picture emerges.
102
Each tier represents a reduction of required information bandwidth to transmit
the same information content and the extraction of higher order patterns. Once the
Tier 2 tactical picture has been formed, the information content may still be so
great that only selected subsets of the data may be displayed or transmitted among
units. This will mean further extraction of patterns and initiation of plans and
goals based upon these patterns.
Within an actual combat system there are many levels of control. The conceptual model categorizes five levels of control corresponding to each combat system
response:
0. Analog (reflexive response): The actual control signal required to implement a specific action, and which is modulated by parametric and mode
control selections.
1. Parametric (considered response): The selection of a mode represents a
domain of parametric control inputs. The selection of specific parametric
control values is performed to optimize the appropriate response to external
stimuli.
2. Mode (creative response): Doctrine translated into a well-defined control
matrix which restricts the modes of operation of the combat system to a
set of predictable responses in support of mission objectives.
3a. Doctrine (closely coupled multiunit coordinated response): Battle Force
Mission Objectives and Rules of Engagement translated into battle group
mission plans, and doctrines which further subdivide the mission goals
into subgoals.
3b. Rules of Engagement (loosely coupled multiunit coordinated response):
The repository of all commands adhered to by each platform from which cooperative response can be formulated to satisfy battle force mission objectives.
The final conceptual element is the ships Battle Management Organization. The
CNO NTDS Functional Allocation Study group defined a generic operator hierarchy which
encompasses all specific operator hierarchies in the fleet. There are four levels
within the command structure as follows:
O. Action Implementers: Operators who perform manual tasks within the sensor
and effector subsystems and are outside of the command action direction
system (CADS).
1. Action Transformer: Operators who provide details required to implement
an action and keep action selectors apprised of the outcome of an action.
2. Action Selector: Operators who recognize the need for an action; define
options and select the appropriate response; and disseminate directives
to action transformers.
3. Action Authority: Command who ensures that actions selected are consistent
with other actions; constraints imposed by higher authority; and broader
force objectives.
103
The above Battle Management Organization overlaps the conceptual tiered combat
system at the interfaces. That is, the "action implementors" perform Tier 0 and
Tier 1 control tasks; "action selectors", Tier 1 and 2 control tasks; "action
selectors", Tier 2 and coordination control tasks; and "action authority",
coordination control tasks and mission planning (figure 6). The action authority
or command is responsible for the direction of the combat system.
Since the conceptual control model presented here allocates functions according
to response, and the CNO study allocates functions according to the combat action
decision maker information requirements, the allocation here of combat action decision
makers to combat action responses provides the isomorphism of functions defined
within each model.
The conceptual model of a combat system presented here (Figure 7) addresses
the combat system information network without considering the physical allocation
of functions to hardware, or the interaction between software elements. As can be
seen in Figure 7, the primary areas of concern to the CDS program are supporting
Command in battle group mission planning and deployment, and multisource/multiwarfare
planning and engagement; not the specific execution of engagement orders and the
like. The CDS as a system component of a distributed Battle Force CDS will also
perform functions to support Tactical Flag and other participating units in Battle
\
CADS
LOOSELY
COUPLED
COORDINATED
CLOSELY
COUPLED
COORDINATED
CREATIVE
CONSIDERED
ACTION AUTHORITY
* ENSURES THAT ACTIONS SELECTED
ARE CONSISTENT WITH
- OTHER ACTIONS.
- CONSTRAINTS IMPOSED BY
HIGHER AUTHORITY.
A- BROADER FORCE OBJECTIVES
ACTION SELECTOR
* RECOGNIZES THE NEED
FOR AN ACTION
* DEFINES OPTIONS AND SELECTS
THE APPROPRIATE RESPONSE.
* DISSEMINATES DIRECTIVES.
ACTION TRANSFORMER
* KEEPS THE ACTION SELECTOR
APPRISED OF THE PROGRESS
OUTCOME OF AN ACTION.
* PROVIDES DETAILS REQUIRED TO
IMPLEMENT AN ACTION.
REFLEXIVE
Figure 6.
The relationship of the Combat Action Decision Makers
to the Tiered Conceptual Control Model within a
Combat Action Direction System (CADS).
104
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Ti
.ATORS
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VC11CA.
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SIT"J1TIOh
\
OIAC,.oo.
EFECTO
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PROCES
R.SPOESE
,ONSE
Figure 7. Conceptual Model of a Combat System
Force Track Management, and will provide composite warfare commander support
including propagation and response to Force Command orders. The other combat
system elements (Tier 0 and Tier 1) integrate sensor and weapon capabilities to:
4.
*
increase the reflexive response effectiveness within well-defined
situations, or
*
increase the considered response options with predictable results.
Delegation of Authority
The issue of the role of Command within the combat system centers upon variant
interpretations of the AIE
Doyle directive
(2)
for
combat system design;
in
particular, Command's delegation of authority in multiwarfare environments. The
salient issue in the delegation of authority is defining the degree of centralization
required for Command to exercise direction. The ADM Doyle concept directs the
delegation of authority down the ship's organizational echelon closer to the sensors
and weapons and the implementation of commands. This achieves a decrease in
response time and in the load upon Command. This delegation of authority requires
that the criteria for exercising control be specific and well defined, and that the
scope be limited. It also requires that Command be given information with which
to assess plans and the implementation of delegated authority. Strict delegation
105
of authority decreases Command's capability to "retain overall control over the
ship's total combat system". Such strict delegation limits Command's capacity to
direct the combat system and, therefore, does not satisfy the intent of the Doyle
directive.
The conceptual combat system model permits simultaneous and independent action
for combatants and warfare areas within a well-defined control hierarchy structure
in which Command exercises broad positive control. Table 1 summarizes the above
three approaches.
TABLE 1
ACDS Conceptual Combat System Model Design
CONCEPTUAL
MODEL
A. Simultaneous or
Tiered Federated
Independent Action in All Combat System Design
Warfare Mission Areas
CURRENT
INTERPRETATION
Partitioned Combat
System Design
B. Delegation of
Authority Including the
Detailed Conduct of
Engagements
Mission Management
Delegation of Authority
Defined by ROE and
Doctrine
Delegation of Authority
Fixed by Design
C. Command Must
Retain Overall Control
Over the Ship's Total
Combat System
Multiware Operational Environment.
Command Exercises
Broad Positive
Control
Control Intervention
as well as Negation
when Necessary
5. Summary and Conclusions
The layered combat system responds to the tactical environment within a hierarchical control structure that provides sensory interactive, goal-directed
behavior; i.e., combines the mission and warfare area commands and objectives with
the sensor data from ownship and offboard sensors to form the appropriate response
to the tactical environment. Such control structures have been the topic of
extensive investigation in the area of brain modeling and robotics. Dr. Albus'
control system theory approach ( 1) provides a framework most analogous to the
control structure of command and control systems. In summary, Albus states that
the sophistication of response and the complexity of behavior resulting from a
control hierarchy depends upon:
106
·
The number of levels in the control hierarchy.
·
The number of feedback variables that enter each level.
·
The sophistication of the control function that resides at each level.
* The sophistication of the sensor processing systems that extract feedback
variables for use by the various control functions.
Advanced combat systems must provide sufficient sophistication with respect
to the spectrum of responses supported so as to increase the number of options that
a potential adversary must account for in planning a tactical action and to defeat
his capability to predict responses and achieve an element of surprise. On the
other hand, advanced combat direction systems must provide command the capability
to restrict the control options within the combat system so as to achieve specific
objectives with some degree of certainty of success.
As the ship's command and control structure becomes more dependent upon
automation to achieve its objectives, these system requirements will become
increasely evident to the combat system designer. It is not the purpose of CDS
design to model or imitate the human brain. However, such paradigms do provide
guidance which should not be ignored within an overall command and control
architecture ( 7). Ultimately this conceptual model will be used to define an
overall combat system architecture which shall be adaptive to changes in threats
and capabilities and permit the continual preplanned improvement of system design.
The authors would like to thank Dr. Michael Kovacich of Comptek Research, Inc. for
his initial insights at the conception of this project which were invaluable in
directing the outcome of the final model. Also the diligent efforts Ms. Mary
Carlson and Ms. Darla Carson in preparing the manuscript and presentation are much
appreciated.
107
References
1. Albus, J., "A Model of the Brain for Robot Control" Parts 1-4, Byte.
Byte Publications, Inc. (June-September 1979).
2. Doyle, Admiral, "(CNO Surface Ship Combat System Operational Philosophy"
SER 03/702528, (5 Nov 1976).
3. "Final Report of the CNO NTDS Functional Allocation Study Group",
(20 February 1981).
4. Kraft, T. and White, D., "Unified Sensor Control: Tier II Control Approach",
Comptek Report: M3352-3-3 (December 1978).
5. "MODFCS Architectural Baseline:
Dahlgren (15 January 1980).
A Combat System Architecture", NSWC
6. NAVSEA 0967-LP-027-8602, Advanced Combat Direction System Design Program
Plan, Volume 1 (June 1981).
7. STS Data Management System Design, Charles Stark Draper Laboratory, MIT,
(June 1970).
108
EVALUATING
THE
UTILITY OF
JINTACCS
MESSAGES
BY
Captain John S. Morrison
United STates Air Force
TacticaZ Air Forces Interoperability Group
Langley Air Force Base
Virginia
109
ABSTRACT
The program for Joint
Interoperability of
Tactical
Command and Control
Systems (JINTACCS) is defining message
standards and operational procedures needed to improve joint
command and control. Within the Air Force, the Tactical Air
Forces
Interoperability
Group
(TAFIG)
is using both
quantitative
and
qualitative
methods to evaluate the
effectiveness of
JINTACCS within the context
of a joint
exercise.
The methods
are based
on a conceptual model of
factors important to military decision making.
110
But don't you see that the whole trouble lies here. In words ,
words . ..
And how can we ever come to an understanding
if
I
put
in
the words I utter the sense and value of things as I
see them,
while you who listen
to me must inevitably
translate them according to the conception of things each one
of you has within himself. We think we understand each other,
but we never really do [Ref. 1].
- Luigi Pirandello
I. INTRODUCTION
A.
THE LANGUAGE OF BATTLE
On the tactical battlefield, the cost of misunderstanding
can
be very high.
The grammer,
syntax,
and meaning of
commands must be communicated with a high degree of precision
in order
to effectively coordinate the use of
people,
weapons, and resources. By its very nature, the battlefield
is a source of ambiguity. Words, procedures, and actions are
often transformed
in unpredictable ways, and are especially
susceptible to noise injected at the joint interface. The
Joint
Chiefs
of
Staff
recognized the importance of
cross-service communication when they established the program
for Joint
Interoperability
of Tactical Command and Control
Systems
(JINTACCS) in
1971.
At
the time,
services and
agencies were not
interoperating. Each service had its own
message
standards and its own terminology. Joint interfaces
and
information exchanges were not
clearly defined. The
language of battle was rife with ambiguity.
B.
THE LANGUAGE OF JINTACCS
The JINTACCS program was established in order to develop
standards and
procedures for
a more effective exchange of
information within the joint task force. These standards and
procedures include:
1.
2.
3.
4.
Message standards which
are designed to be man and
machine readable.
A
Message
Element
Dictionary,
to insure that
information is understood by all players.
Interface operating procedures, to insure that the
right
messages go to the right people at the right
time over the right communications.
Data
standards,
to
insure
that machines and
111
communications work together.
JINTACCS is the new language of battle. It is a synthetic
semantic and procedural
syntactic,
containing
language
experts,
by operational
developed
was
It
components.
(and will
It has been
committees.
joint
engineers, and
laboratory and field
in
both
tested
be)
to
continue
order to determine its acceptability as a
in
environments,
for human-human, human-machine, and machine-machine
standard
information exchange.
hierarchy of information
address a
JINTACCS standards
is the
element
information
primitive
most
The
levels.
the
for example, mark
characters,
Special
character.
of
level
This
"sets."
and
"fields"
of
end
and
beginning
for
than
machines
for
important
more
is probably
information
groups of characters form key
level,
the next
humans. At
Key words are entered into a
words, and convey meaning.
for "fields"; semantically
rules
according to the
message
"sets"; sets are combined
form
to
related fields are combined
logically related
of
groups
Finally,
to form messages.
messages form "strings."
JINTACCS is more structured
"grammar" of
Although the
than what most message preparers are familiar with, it is
1 shows an example of an
also more consistent. Figure
existing message standard, while Figure 2 shows the same data
formatted as a JINTACCS message. To the extent that existing
and acronyms, the
abbreviations, codes,
messages rely on
is roughly comparable. It should be
readability
degree of
does permit free format
that the JINTACCS standard
noted
to capture as much
attempts
but the standard
entries,
as possible in the "structured" portion of
significant data
are two reasons for this. First, of
the message. There
it easier for machines to process
makes
course, formatting
of the message
"logic"
the data. Equally important, the
available, must be
if
information,
demands that critical
included.
While JINTACCS can be viewed as a linguistic problem, it
to view it as a communications engineering
also useful
is
problem. Weaver [Ref 23 distinguished between three levels of
communications analysis. Level A deals with the accuracy with
be transmitted. (The
communication can
symbols of
which
B deals with the precision with
Level
problem.)
technical
the transmitted signals convey meaning. (The semantic
which
C deals with how effectively the received
Level
problem.)
(The
way.
desired
the
in
conduct
affects
meaning
of
theory
mathematical
The
problem.)
effectiveness
A, while
33 deals only with Level
[ Ref
communication
JINTACCS cuts across all three levels of communication. New
tools must therefore be forged in order to properly evaluate
JINTACCS.
JINTACCS,
shows the relationship between
3
Figure
analysis [Ref 33, and communications engineering.
linguistic
linguistic side, we can view JINTACCS in terms of
On the
112
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"competence"
(How much do operators know about JINTACCS?),
"performance"
(How
well
do operators use JINTACCS?),
"'grammaticalness" (Are there any inconsistencies in the rules
that specify the well-formed strings of minimal syntactically
functioning
units
(formatives),
and assign structural
information to those strings?), punctuation, and spelling.
Interface
operating
procedures
can
be
viewed as a
metalanguage dealing with messages
(Fig. 4); the messages
themselves form another linguistic level with distinct rules
for
well-formedness; the character set represents the lowest
linguistic
level. On the communications engineering side, we
can view the effectiveness
problem in terms of interface
operating
procedures, the semantic problem in
terms of
message information content,
and
the technical problem in
terms of the message character content.
Very broadly,
the communications engineering aspect of
JINTACCS deals with the rational determination of capacities
and
boundary
conditions,
while
linguistic
analysis
empirically measures the well-formedness and appropriateness
of
messages and message strings. We must view both faces of
JINTACCS in order to see the whole picture.
D.
THE JINTACCS APPROACH
In order to make testing manageable, JINTACCS has been
divided into five segments:
intelligence, air operations,
operations
control,
fire support,
and amphibious.
Each
segment
is
evaluated
in
two
phases:
compatibility/interoperability
testing,
and the operational
effectiveness demonstration.
Compatibility/interoperability
testing
evaluates
JINTACCS
in a controlled
laboratory environment,
using
representative
operational
facilities
and
commercial
communications
channels.
The "compatibility" portion of the
test
evaluates
the
ability
of
systems to exchange
information;
the
"interoperability"
portion
of
the test
evaluates the ability of operational facilities to use the
information.
Testing
is geographically decentralized, with
the
principal
USAF test unit
located at
Langley AFB,
Virginia;
the
Navy test
unit is here at San Diego,
California;
the Marine Corps facility is at Camp Pendleton,
California; and the NSA test unit is at Fort Meade, Maryland.
The Army test unit, and the Joint Interface Test Force are
located at Fort Monmouth, New Jersey.
After
compatibility
and
interoperability have been
tested,
and
JINTACCS standards have been modified to
accomodate improvements recommended
by the services and
agencies, the JINTACCS segment is turned over to CINCLANT for
an operational
effectiveness demonstration (OED). The OED,
which
takes place within
the context of
a SOLID SHIELD
exercise using full-up facilities, insures that the developed
standards
work
in
a
tactical
environment.
The OED
demonstrates JINTACCS compatibility
with current tactical
communications, and further refines messages and operational
115
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procedures.
JINTACCS is an ambitious program which is essential to
the success of future joint task force efforts, but it is not
Since JINTACCS redefines the very fabric of
without risk.
a scientific and methodical
command and control,
tactical
approach is needed to evaluate the effectiveness of JINTACCS,
insure that the program is on
isolate problem areas, and
Such an approach must be based on a conceptual model
target.
and factors important to such
military decisionmaking,
of
reports on JINTACCS message
This paper
decisionmaking.
Air Forces
evaluation methods developed by the Tactical
at Langley Air Force Base,
(TAFIG),
Interoperability Group
The methods are being used to analyze the results
Virginia.
of
the JINTACCS intelligence OED, which occurred in May of
this year.
118
II.
A.
INFORMATION BASED DECISIONS
GEDENKEN EXPERIMENT
Consider
the
following
"thought"
experiment:
A
A, waiting to receive
decisionmaker
sits in command post
messages of a particular type from command post B. Under the
"old"
received
messages contain
scenario,
all
first
relevant
to
the
which
is
no
longer
information
As
a result, no decisons are made,
decisionmaker's task.
the
the second
scenario,
based
on the messages. Under
action,
but
call
for
not
individually
messages
do
collectively point to a possible environmental state which
After a certain point, a pattern
could
necessitate action.
emerges,
and
the decisionmaker makes a decision about the
true state of the environment. Under the third scenario, each
indicate that an
contains
data which
clearly
message
Decisions are made
response
is appropriate.
immediate
immediately after messages are received and processed.
"decision"
in the above
Regardless of
how we define
decisions are based on information acquired
experiment,
if
from messages, and if the message preparer at command post B
it
is clear
that message
had
key data
to communicate,
preparation, transmission and processing times place an upper
limit on
the "rate" at which decisions can be made (Fig. 5,
Dk ).
Another conclusion which can be drawn from an analysis of
point
in time that a
the experiment
is that the actual
is partially determined by message
decision may be made
the content of a particular message
content.
For example,
some future time, after
figure into a decision at
could
additional
data is acquired (Fig. 5, Dj). Alternatively, the
content
of the message could be useless for decisionmaking
no decision would ever be made based on the
purposes, and
message. This latter possibiity represents the lower bound of
the decision rate (Fig. 5, Di).
is that the
conclusion from the experiment
A third
messages
provide a "schema" for information, independent of
the information
itself.
The value of the message (which is
distinct
from the value of
the information content) is
the message conveys
by how well
determined
partially
information critical to the decisionmaker's job, if and when
such information is available.
if the message is garbled, or if the accuracy
Fourthly,
suspect, then the decisionmaker may
of
the
information is
have to integrate data over several messages before arriving
119
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at a conclusion. Garbling is a function of both channel noise
and human error; the degree to which the information content
of
a message represents ground truth is determined by the
sensors to resolve the environment, and by the
ability of
ability of humans to form accurate judgements.
EB.
DECISIONMAKING CAPACITY OF A MESSAGE
For purposes of making operational decisions, the message
field
is the basic unit of information. We assume that if a
field is critical to the operation, is syntactically correct,
and
contains accurate information, then it may be used as a
basis for making reasonable decisions (Fig. 6). The number of
such fields in a message is given by:
D
Where
H
A
I
=
=
=
=
HA-I
critical fields in a message
proportion of syntactically correct fields
proportion of fields containing accurate
information
Intuitively, it
would
seem that the number of usable
fields in a message would influence the number and quality of
decisions that could
be made, based on that message. This
hypothesized relationship
between semantic components and
decisions parallels
a relationship, found at the technical.
level, between information and control: The degree of control
of
a system is proportional to the logarithm of information
in
the system
[ Ref. 53. While the "bit" is an appropriate
of measure for information at Weaver's "Level A," it is
unit
less
appropriate for levels "B" and "C," and will therefore
not be used.
The usable fields in a message may be weighted for each
operational
facility
or
function,
depending on
what
proportion of
the total critical information requirement is
satisfied by a single, usable field C Fig. 73. For example,
if,
looking across
all
messages, the critical information
needs of
an operational
function can be satisfied by 100
message fields, then each usable field would contribute 1/100
of the total requirement. We assume that a message type which
is capable of
contributing
65/100 of
the total critical
information requirement is more valuable than a message type
capable of contributing only 3/100 of the total. The weighted
number of usable fields in a message is found by
N
Where
F
=
Total
operational facility.
=
H*A*I / F
number
121
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to provide a measure of
can
be broadened
The result
"usefulness" extending across all operational facilities and
functions. Let F' be the number of elements in the set of all
message fields which are critical to one or more operational
let H' be the number of elements in the subset of
functions;
by fields contained in message type Q; let A' be
F' formed
accuracy of the message across all
the average syntactical
operational facilities; and let I' be the average accuracy of
operational
across all
information content
the
message
the total information
of
facilities. Then the proportion
needs of the C3I system satisfied by message Q is given by
N'
=
H
'
A' · I' / F"
The
expected maximum rate, Bq, at which messages of type
information from the message
communicate critical
Q can
depends on the sum of the
to the decisionmaker
originator
processing
transmission and
average message preparation,
times (Tm, Tt, and Tp, respectively):
1
Eq
=
Tm + Tt + Tp
zero, then
terms in the denominator are all
If
the
an
could be communicated at
information
theoretically,
fast rate. If the sum of terms in the denominator
infinitely
(for example, if the total message
is effectively infinite
the military operation under
the length of
delay exceeds
consideration), then no decision could ever be made, based on
The absolute rate at which information can be
that
message.
less important than the communication rate
communicated
is
relative to the pace of the operational environment. There is
a difference between "decision time" and "time by the clock."
This difference can be taken into account by differentially
weighting time delays for different operational functions,
for different messages. For example, if a reconnaissance
and
(WOC-R) must transmit the mission
wing operations center
report (MISREP) within 60 minutes of aircraft engine shutdown
the message is sent via immediate precedence
and
if
time,
less than 60 minutes), and if the
(required delivery time
at the Tactical Air Control Center (TACC) is to process
goal
within
30 minutes of
(update the data base)
the MISREP
then the maximum recommended delay for
message receipt,
information from the WOC-R to the TACC is 150
communicating
"weight" given each minute of observed delay
minutes. The
would be 1/150. That is, one minute equals 1/150 of "decision
time."
The ratio of allowed communication time to observed
124
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the rate of
communication with
communicaton time gives
respect to the pace of the operational environment.
Using the above results, a figure of merit (FOM) can be
JINTACCS message. This FOM is a
derived for each type of
of
certain
measures of
effectiveness which
composite
(intuitively) relate to the usefulness of the message as a
decisionmaking tool. For a given type of message, Q
H' fm
FOM
(Q)
=
+
tP1+r
-
A
F
'
I'
L Tm + Tt + Tp
rp
Where
rm,
7ft, and
are the time goals for message
preparation,
transmission and processing, respectively. The
FOM is the weighted product of usable fields and Bq. It can
proportion
of
total
be
interpreted as the theoretical
per weighted unit of
critical
information needs satisfied
time.
I II. EXERIMENTAL METHODS
An operational exercise using JINTACCS can be viewed as a
to the
linguistic
experiment.
Training sessions prior
operator competence; measurements taken
exercise establish
to determine operator
during the exercise can be used
structured
questionnaires
and
performance;
subjective
interviews can be used to evaluate the acceptability of
JINTACCS, as viewed by operators who must read it or write
it.
Figure 9 shows the three dimensional collection space for
is being
used
to
observations,
which
JINTACCS-related
evaluate the results of a recent joint exercise. The vertical
represents different operational facilities which
dimension
exchange information. The horizontal dimension represents the
variety of
messages to be evaluated. The third dimension
represents observations collected over time. A single cell in
represents a particular
the
three
dimensional
block
occurrence of
a particular type of message generated by a
particular operational facility (OPFAC). Analysis of variance
(ANOVA) will
be
applied to time and error data collected
in order to highlight those results
during the exercise,
could not
reasonably be attributed to chance. ANOVA
which
will
also allow us to trace the source of a statistically
significant result (OPFAC vs message).
IV.
CONCLUSIOUNS
We do not expect to have the complete results in from the
joint
exercise until the end of this calendar year. However,
126
A-7
127
we have nearly completed our analysis of critical information
requirements,
and we anticipate that several proposals to
change
the JINTACCS standard will be submitted as a direct
result of this analytical effort.
not
go away, but it will
The JINTACCS standard will
continue to evolve to meet the needs of the services and
agencies. The Tactical Air Forces Interoperability Group is
contributing
to this process by developing a quantitative
approach to C3I.
128
IBL I OGRAPHY
1. Luigi
Pirandello. Nake
Masks, "Six Characters in Search
of
an Author" (New York: E. P. Dutton & Co., Inc., 1952), p.
221.
2.
Warren
Weaver. "Recent Contributions to the Mathematical
Theory
of
Communication,"
bThe
athematical
T.heor
nf
Communicatioro
(Urbana:
The University Of
Illinois Press,
1969), p. 4.
3. Noam Chomsky. Aspects of the Theory -o_ Svntax
The M.I.T. Press, 1965)
(Cambridge:
4.
Appendix 5 to Annex Y to AFLANT JINTACCS Intelligence OED
Plan
(u),
AFLANT Supplemental Data Collection and Analysis.
HQ USAF Forces Atlantic
Command,
Langley Air Force Base,
Virginia 23665. 15 January 1981.
5. W. F. Duckworth, A. E. Gear and A. G.
Operational
Research
(London:
Chapman
190.
129
Lockett.
_ t.tid
to
and Hall, 1977), p.
130
FIRE
SUPPORT CONTROL AT THE
FIGHTING LEVEL
BY
Barry L. Reichard
United States Army
BaZllistic Research Laboratory
ATTN: DRAR-BLB
Aberdeen Proving Ground, Maryland 21014
131
Fire Support Control at the Fighting Level
Barry L. Reichard
U.S. Army Ballistic Research Laboratory
May 1981
. 'INTRODUCTION
A strong National Defense capability depends upon the ability of our US Army to
respond to any type threat in any theater in the world. One of the most demanding
missions is fighting against a mechanized threat where greatly increased mobility and
lethality combined with the possibility of fighting outnumbered will result in an intensity of battle never experienced on previous battlefields. The Yom Kippur War was a
sample of the kind of intensity of battle that can occur on the modern mechanized
battlefield.
The objective of the US Army, however, remains unchanged - to win the land
battle. Doing this on the modern battlefield, especially when outnumbered, will
require the skillful orchestration of combined arms teams to concentrate combat
power where and when it is needed most. On this dynamic battlefield, where command communication lines may be cut off intermittently, the battle must be fought
and combat power must be applied by Captains and their companies, batteries, and
troops under the general direction and control of brigade and battalion commanders
(while higher levels of command should focus on concentrating the forces at the right
time and place). Since a principal component of combat power is the firepower provided by the fire support system (Figure 1), the ability to plan, coordinate, and execute fire support at the fighting level must be a critical area of concern for US Army
Research, Development, and Acquisition.
As evidenced by Figure 1, the fire support system is quite complex in that it consists of many parts with a wide variety of capabilities and operations, is widely distributed geographically over the battlefield, and has elements at all command levels and
some from other services. Surprisingly, a little known fact (to nonartillery-men) is that
the field artillery is responsible for integrating all fire support into combined arms
operations as well as providing one form of fire support. In fact, it is because of the
current field artillery organization and command structure that the lowest level at
which integrated fire support for the fighting elements can be examined is the
maneuver brigade.
Normally, an artillery battalion (bn) assigned the tactical mission of direct support
(DS) is used to provide fire support coordination assets and artillery firepower to a
maneuver brigade (bde). (Depending on assets available and the tactical situation,
another artillery battalion may be assigned the tactical mission of reinforcing to augment the fires of the DS bn.) A DS bn is still under the command of the next higher
artillery force headquarters (HQ), division artillery (DIVARTY), but answers calls for
fire in priority from the supported unit, DS bn forward observers (FOs) and target
132
acquisition means (e.g., radars and air observers), and last from higher force artillery
HQ; i.e., a DS unit is the on-call artillery firepower for the supported maneuver brigade. If the brigade needs more fire support than that already available organically or
through artillery fire support facilities, additional fire can be requested from
DIVARTY which for a mechanized infantry or Lrmor division, includes two additional
DS bns (for other maneuver bdes in the division), one general support (GS) bn, and
a number (perhaps three) of battalions attached from corps in the form of an artillery
brigade. The counterfire mission (attack of enemy indirect fire systems) is largely
accomplished by DIVARTY and the attached artillery bde, wheres close (fire) support
(attack of "close" enemy troops, weapons, or positions that threaten the force) is usually provided or arranged by DS artillery or organic mortars in support of maneuver
brigades, the fighting elements.
The fire support control facilities in a type mechanized infai-try brigde are depicted in Figure 2. Fire support control is defined here to mean all operations necessary
to cause the right fire support effect to reach the right destinati"n at the right time,
which therefore includes what is now called fire support planning and coordination and
fire direction as well as control of devices to guide munitions to the target, e.g., laser
designators. Fire support planning is the continuous process of analyzing, allocating,
and scheduling fire support Fire support coordination is the process of implementing
that plan and managing fire support assets. Fire direction (FD) is the employment or
execution of fire support firepower and can be either tactical or tIhnical. Tactical fire
direction is the selection of targets to be attacked, choice of fire Support units to fire,
selection of the best ammunition, and (with TACFIRE) corside-tion of fire support
coordination measures. Technical fire direction is the conversion of calls for fire support (target location and type) into fire commands (aiming data) a as some think of it
- solving the gunnery problem.
In the brigade area (Figure 2), artillery fire direction is performed at the DS bn
fire direction center (FDC) and at each of the battalion's batteriyDCs A, B, and C.
Both 81mm and 107mm (4.2 inch) mortars are organic to man-euer units - an 81mm
section of three weapons to each rifle company and a 107mrm pla1-on of four weapons
to both mechanized infantry and tank battalions. Mortar FDCs are commanded by the
maneuver unit commander, but the artillery fire support coordinaiors (FSCOORD) are
responsible for integrating mortars into the fire support p!an Ez for advising the
maneuver con.mander on their use. As with artillery FDCs, th establishment and
operation of fire support planning and coordination facilities are t-e responsibility of
and the mabrity of personnel and equipment are provided by'hl field artillery. At
each echelon from corps to company, a FSCOORD is responsi-_'to the supported
force commander for inte:r-ating all fire support means into the -e ssuport plan and
for advising the force commander on how to implement fire suppct. The FSCOORD
is either the commander of the supporting artillery unit or a reprR-.ntatrve thereof.
In the illustrated br-i]-de area, the bde FSCOORD is the CS art-iery bn commander, usually a LTC. The bde fire support planning and coOr-nation facility, the
fire support element (FSE), is operated by the bde fire support offetr (FSO, a MAAJ),
the FSCOORD's full-tirme representative, and three enlisted men, and it works in
133
coordination with the bn FSEs (whose FSOs are supervised by the bde FSO), with the
DS bn FDC, and with the main and tactical FSEs at the division command post (CP).
At brigade and every level from battalion to corps, representatives of other fire support means are made available to the FSCOORD as shown in Figure 3. The bn FSO
(a CPT) is the FSCOORD at the maneuver battalion level, and like the bde FSO, he is
the principal advisor to the force commander (maneuver battalion commander in this
case) on all fire support matters, recommends allocation of fire support, prepares fire
plans, performs target analysis functions, and monitors requests for fire support. The
bn FSE must coordinate its work with the fire support teams (FISTs), which are
supervised by the bn FSO, other bn FSEs, the bde FSE, and the DS bn FDC.
At the company (co) level, the FIST is the fire support organization. The FIST
concept was recommended by the Close Support Study Group in 1975 to optimize
observed fire support, and subsequent to Department of Army approval in 1977, has
been phased into the force structure. Simply stated, the FIST concept combined the
mortar and artillery FO organizations, called for new equipment like tracked armored
personnel carriers (for FISTs working with mechanized units) and additional radios,
and provided for training under a common military operational specialty (MOS). A
"type" mechanized rifle company FIST includes three 2-man platoon FOs as well as a
HQ manned by the FIST chief (a LT) and two enlisted men. Tank company FISTs do
not have these platoon FOs or 81mm mortar sections. (If one of the maneuver bns in
the mechanized infantry bde is a tank bn or if there is a mix of mechanized rifle and
tank companies, the platoon FOs and 81mm mortar FDCs would be deleted in Figure
2.).
With the FIST concept, the additional role of fire support planning and coordination has been added to the traditional FO role - target acquisition and adjust-fire "sensor." The FIST chief (CH) is the company commander's FSCOORD as well as the
primary FO for the company. The FIST, under the supervision of the CH, is responsible for locating targets and requesting and adjusting fire on them, planning and coordinating fire support, reporting battlefield intelligence, and at times, locally controlling
other fire support measures such as close air support.
11. FIRE SUPPORT CONTROL - FUTURE
Tn the future, fire support control development till be impacted by and in turn
will impact the majr rethinking of time-honored artillery organizations, operations,
and doctrine as the Army enters the high-technology automatic data processing (ADP)
wvorld. The new Flre Support Team (FIST) organization concept, for example, is
already bEing implemented. This combination of the artillery and maneuver-unit mortar observers has raised the fire support control issue of twhether the FIST chief can be
both the primary observer and the comnpany-level fire support coordinalor
(FzSCOORD) and has generated a nerw fire support control materiel requirement for a
spcia FIST Digital IMessaSte Device (DMIND) to permit the monitoring, editing, and
automatic retransmission of data commnlunictions. One result of the Division Restructure Study (DRS) of 1976 is that the direct support artillery battery size will increase
134
from six to eight guns that will normally operate as two four-gun elements, both with
fire direction capability. Fire support control for the DRS battalion fire direction
center (FDC) will then involve interaction with six instead of three (for a 3-btry bn)
subordinate fire-unit FDCs, each of which will have a Battery Computer System when
it is fielded. The Division 86 Study organization, when implemented, will also have a
serious impact on the fire support control system in that ten maneuver battalions
instead of nine in a heavy division and four companies instead of three must be serviced by the fire support system.
The combined-arms Close Support Study Group IT (CSSGII) recognized that in
the new Tactical Fire Direction System (TACFIRE) data world, there was an operational need for not only the FIST DIMD but for a functionally similar device for the
battalion (bn) fire support elements (ESEs) in the maneuver brigade area. (The need
for such devices will be especially critical when the mortar FDCs receive the Mortar
Fire Control Calculators (NlFCC), which operate in the data world.) Such data devices offer the promise of real- time fire support coordination as opposed to silence-isconsent. For example, as shown in Figure 4, the FIST DMD (at FIST HQ) can serve
as a data communication switch, a decision node controlled either actively by the
operator or automatically as preprogrammed, to direct a FO generated fire request
either to the organic company mortars or to the bn FSE for a higher level of fire support depending on the tactical situation, target type, or other criteria. With a new data
device in the bn FSE, the organic bn mortars or higher fire support means can be
selected at this decision node.
In consideration of future Field Artillery Tactical Data System (FATDS) requirements, the TACFIRE TRADOC System Management Office (TShMO) continued this
preferred centralized control scheme (which is actually a distributed processing system) to the bde FSE At this point, service of the fire request could be allocated to
fire support means represented in the bde FSE, e.g., close air support (CAS) sorties or
naval gun fire (NGF), or could be passed on to the direct support (DS) field artillery
bn I-DC, which in turn could select the appropriate battery or batteries or perhaps
request a reinforcing battalion to fire the mission. To remove the target intelligence
load on the bn FDC, the TACFiRE-TSMO also added a new element in the bde-area
picture - the target integration center (TIC). Interfaced to the Firefinder radars,
Remotely Piloted Vehicles (RPVs), and other new-technology target acquisition devices, the TIC with ,ADP aids can convert voluminous target intelligence data to
confirmed target.data for insertion into the active fire support control 'circuit" - and
thereby reduce the data load on that circuit and the brigade-area fire support control
system.
The fire request routing depicted in Figure 4 raises many issues, but the primary
one undoubtedly is responsriveness. The need for the flexibility, i.e., the capability to
short-circuit the preferred centralized scheme (for incresed responsiveness), was
rccognized by the CSSG TI. The data communications needline as tabulated in tihe
CSSG It report, shows the desire for full fIexibility - to be able to operate optionaUly
with successively lorwe.r levels of centralization (Fi'ure 5) and even fully decentralized
control where the FO can direct his fire request to any fire support control element
135
from the FIST HQ to the bn FDC (Figure 6). As indicated in Figure 6, it may even
be desirable to permit, under some circumstances, the FO to deal directly with a preallocated weapon system for maximum responsiveness. The need for responsiveness is
obvious, but there will also be crucial times when the force commander needs to be in
full (centralized) control of the fire support forces, e.g., final-protective-fire massing
and special tactical counter-force interdiction. If the preferred control system is
designed and developed appropriately, all lower levels of control will be possible from
a materiel standpoint, and commanders will have the option of selecting the most
appropriate one for a particular tactical situation.
Continuing with the rethinking of fire support control, a recent Field Artillery
School draft doctrinal paper presents a potential generalized philosophy for fire support
control in the 1985-2000 time frame. Citing the volume of targets that will be generated by new target acquisition devices (in one scenario simulation, an average of
1586 target complexes are acquired in one DS area in 24 hours) and the potential
shrinking numbers of friendly weapon systems (together with growing numbers of
enemy weapon systems), the paper recognizes that fire support assets must be time
shared. The current approach to this problem has been face-to-face and voice cornmunications and the use of ADP to automate manual procedures. The paper, however, presents a force design that will allow maximum exploitation of ADP technology, which is still growing at a rapid pace, and the emerging automatic data distribution technology.
Tn this concept force design, the fewest possible weapons (1 to 4 recommended)
are organized into a fire unit (FU) that has its own technical fire direction and
positioning/pointing sysaem (probably on each weapon). Back-up technical fire direction could be performed by a handheld calculator, or an adjacent weapon. The
weapons in the FU would be dispersed and perhaps perform single-weapon missions
with a gun-and-run tactic. Gun and run (or shoot and scoot) presents the toughest
control problem and nearly the same on-board fire support control is needed for
widely dispersed or gun and run tactics; therefore, gun and run should be pursued - if
the system is designed for gun and run, all lower flexibility options are possible,
including massed fire. The weapon(s) in a FU should operate within a 3-km position
extent and use "hide" areas for resupply. (However, a single hide area for many
weapons may be detectable by the enemy.) Location and weapon status would
automatically-be transmitted to the battery that will be discussed below.
For higher-level fire support control FUs would be organized into a battery,
which would have a stable organization in peacetime, but would be task organized
awhen committed to combat. As shown in Figure 7, the battery is divided into tvo
main parts: the battery trains element and the operations (OPS) element. The OPS
element is normally located at the maneuver bn command post (CP) to expedite the
intearation of fire support and maneuver fires. In lieu of the traditional btry FDC, the
OPS element performs fire support planning and coordination and tactical fire direction, coordinates FLI movements, and also serves as a back-up technical fire direction
system for subordinate FUs. The btry trains element is the principal ammunition and
fuel resupply source for the FUs; the element also provides mess, maintenance,
136
battlefield recovery, and other logistic services. The ADP hardware at the btry trains
HQ, which normally is used to coordinate, monitor, and direct logistics support,
should be identical to the OPS ADP system so that the trains ADP system can serve
as a back-up OPS unit.
For force control, conceptual batteries are organized into battalions, which also
should be task organized in combat. The battalion, like the battery, is divided into an
OPS and a trains element. The OPS element would be located at the bde CP, would
provide tactical control of the batteries, and also would serve as the artillery sensor
integration and target center for the bde command element. The bn trains element
would perform administrative and personnel services, but the principal logistics role
would be to coordinate outside logistics support for the battalion. The conceptual
DIVARTY and corps artillery units would provide neither administrative nor logistics
support but rely on the supported force for this. The DIVARTY and corps units
would have OPS elements at both main and alternate CPs. The OPS units would
recommend task organization of subordinate forces, also serve as artillery sensor
integration and target centers, and perform nuclear and chemical fire planning for the
supported force. A comparison of the current and proposed force design concept is
provided in Figure 8.
Recent Enhanced Self-Propelled Artillery Weapon System (ESPAWS) analyses
(at BRL and ANMSAA) indicated that new-technology materiel concepts may permit
and require significant changes in artillery organizations and operations. Assuming
FOs request fire from the DS btry FDC and then deal directly with a single gun (with
perfect C3), using a generic autonomous gun concept (single-gun missions with gun
and run) with fire-and-forget munitions for DS, and using fire-and-forget rockets or
8-inch munitions in general support (GS), the analysts showved that two battalions of
such weapon systems could support a division force significantly better than the more
standard seven battalions of existing weapons in terms of point targets (APCs, tanks,
and artillery weapons) killed in a mechanized threat. This does not mean that the
division-slice force should be reduced to two battalions, but that with new materiel
and operations concepts, it is possible to have artillery force reserves for nonlethal
roles, interdiction, and massive suppression - if the fire support control system can
accomplish this kind of diversified application of artillery firepower (and other fire support means).
Regarding materiel, the AD)P technology "dish" is overflowing. General requirements for the concept force design described earlier are summarized in Figure 9: distributed common data base, software with interactive query language and the flexibiity
for personal programming and "what if" war gamining, and common hard-are with
graphics displays and tailored hard-copy ouriput formats. The technology either exists
or is emerging to meet these requirements. Micro-computers are getting smaller and
smaller but yet more powerful and equally affordable. Large, flat display systems and
voica recognition te-.hnologies are emerging
. Artificial intelligence, gaming theory,
and distributed decision process-s research can be applied in the software to aid in putting the "man in the loop" without critically degrading responsiveness. At least t-wo
alternative automatic data distribution systems (ADDS) are under development: an
137
enhancement of the developmental Position Location Reporting System (PLRS), a
time division multiple access (TDMA) system, under the control of a centralized computer, with a finite number of unique 'slots" for data transmission, and (2) the Packet
Radio, an experimental system that "marries" a radio and a microcomputer, forms data
communications into "packets," and automatically distributes them.
To exploit new ADP technology and to meet future user needs, an Advanced
Field Artillery Tactical Data System Program Plan has been developed. This modular
"product improvement" plan will permit sequential performance improvements so that
the utility of the current hardware and field capability over the next 15-year period will
be maximized. Moreover, with this approach the system software can be built upon
and refined as opposed to a new start. The improvements will be developed in three
discrete steps: (1) development of a new communications control system (CCS),
which will be programmable to handle a variety of message structures and all communications systems to include dedicated ADDS radios, (2) development of new
remote terminals, which will employ interactive graphics and provide distributed processing and data bases, and (3) development of new, smaller, simpler to operate subsystems for the TACFIRE FDC computer group.
111. FIRE SUPPORT CONTROL TEST BEDS
F:ELBAT-8 & ACE
Recent battle simulation analyses and field experiences have shown that fire support contrgi (or as it is usually referenced, artillery command, control, and communications, C ) is the key to improved fire support effectiveness and survivability. New
fire support control doctrine and evolving user requirements are indicating the need
for both fully centralized and fully decentralized control of fire support and all levels in
betuween, so that control can be quickly tailored to tactical needs. With the automatic
data processing (ADP) technology and concepts "dish" overflowing, the fire support
control development problem can be compared to "boarding a speeding (technology)
train" (in the context of an 8 to 10 year materiel development and acquisition cycle).
Test beds like the periodic HELBAT (Human Engineering Laboratory Battalion
Artil!ery Test) field exercise can help in this problem area by providing a "vehicle" for
he development and evaluation of alternative total oDerating system concepts and procedures. In light of the above introduction, it is no surprise that the main thrust of
HETLBAT 8 will be C 3 as indicated by the priority list (Figure 10), which was generated by the Field Artillery School at Ft. Sill. Further, with new doctrinal concepts
like spread-battery emplacement, split 8-gun battery, and gun-and-run, there is a need
to evaluate new tactical fire direction concepts at the battery level and automated positioning, pointing, and technical fire direction control on board the weapon. W5¥ith the
rapidly increasing need for and the difficulty of distributing data on the battlefield, as
evidenced in IR--BAT 7, there is a need to evaluate data distribution concepts and
w\vavs to reduce the data load such as use of the targiet inte.ration center (TIC), which
will convert the great magnitude of intelligence data to a smaller volume of conrfirrmed
133
target data. With reference to line-of-sight (LOS) limitations experienced with forward observer (FO) vehicles in past HELBATs, concepts for increasing the observation capability from the fire support team (FIST) vehicle as well as air observer capabilities are to be evaluated. Since nuclear, biological, and chemical (NBC) protection
is also a priority item, particular attention will be given to this area including, if possible, the incorporation of NBC protection on some of the hardware concepts fabricated
or modified for HELBAT 8.
New technology concepts to be evaluated in a fire support control system context
should be compared with the newly fielded Tactical Fire Direction (TACFIRE) system
as a baseline. The exercise should therefore be, at a minimum, in the context of a
maneuver brigade-area since this is currently the lowest level of TACFIRE tactical fire
direction and the smallest integral fire support control area (see Figure 2). This will
require the following type "players" in the exercise: FOs, FIST HQs, battalion (bn)
and brigade (bde) fire support elements (FSEs), battery (btry) and bn fire direction
centers (FDCs), weapons, and perhaps company (co) and bn mortar FDCs. Considering this complexity and the high-technology experimental equipment involved, HELBAT 8 will be quite an ambitious undertaking for a one-time 6-week exercise. To
insure maximum usefulness and lasting significance, the exercise must be planned in
as much detail as possible and be approached and followed with a set of integrated
efforts as shown in Figure 11.
One of the first efforts will be the development of a fire support control simulator
(a computer-based laboratory test bed), called the Artillery Control Experiment
(ACE), to aid in the planning of HELBAT 8 and subsequently to serve as a continually available tool for the development and evaluation of fire support control technology, materiel, organizations, and operations. With ACE, fire support control problems
can be identified, analyzed, and defined in a series of alternative system and scenario
contexts, which will be quite helpful in generating and evaluating experiment designs
for HIFLBAT 8. Further, hardware, software, and "skinware" (human interface) technology and system concept opportunities can be explored without building complete
dedicated hardware. Perhaps most importantly, ACE can be used to investigate the
application of key research areas (such as artificial intelligence, gaming theory, and distributed decision processes) to the tough problem of fire support control automation.
As well as providing a much needed tool for user development and evaluation of alternative organization and opzration concepts, ACE may also be used as an automated
command-post-exercise (CPX) trainer. General examples of possible ACE investigation areas include: computer assists at decision nodes, improvement of man-machine
internaces (e.g., natural and query languages), "intelligent" filtering of information
presented to fire support officers (FSOs), and short-hand graphics for responsive,
simplified operations.
More specifically as described in Figure 12; ACE is an interactive, real-time,
multi-player fire support control simulator. Initially it will be developed on an inhouse computer system (a Ballistic Research Laboratory PDP 11/70 with UNIX operating sofrtwar), but wherever possible, a common programming language (such as
FORTRAN) will be used to facilitate the ease of ex-porting ACE or parts thereof to
139
other organizations. ACE will be able to both accommodate and simulate tactical fire
support control materiel, e.g., the TACFIRE Digital Message Device (DMD).
Through simulation, tactical equipment availability problems can be avoided; "what if"
changes can easily be incorporated and evaluated; and training spin-offs are possible.
Through the accommodation of actual equipment, the time-consuming development
of simulator programs can be avoided; hybrid mixes of actual and simulated conceptual equipment are possible; and automatic scenario-loaded testing could be performed. To tie all the system components (actual and simulated) together, i.e., to
model the network and to characterize realistic communications queues and delays and
simulate full-force scenario loads, a supervisory ACE program is being developed.
ACE has been established as a major effort and to effect integration, ACE personnel are actively involved in major HELBAT-8 planning meetings. Production
M emiltoi
pri-gi-amh is heail; conripleled. The
DMDs have teeii Tcquired anid a "DMD
FIST DMD emulator and ACE supervisory programs are currently being written. Battery Computer System (BCS) software and hardware documentation has been
acquired, and a BCS simulator program is being developed to simulate input and output queues, queue management, message interpretation and generation, and functional
time delays such as processing time and operation and polling of the gun display units
(GDUs). When operating equipment can be made available, an actual BCS wiil be
interfaced to ACE to develop a BCS operator training plan for HELBAT 8 and to run
some planned I-ELBAT-8 mission profiles. An example of the output of the DMD
emulator is shown in Figure 13. Once the DMD program is called up, the
commercial-terminal CRT (cathode ray tube) display provides keyboard responses
identical to those of an actual DMD. The figure shows the DM1) status display as
filled out interactively by the operator and shows the movable cursor at the keyboard
bell volume position.
In the near future, ACE personnel will interface an actual DMD to the computer
system and will work with Field Artillery School personnel to develop initial scenario
and experiment designs and with Army Communications-Electronics Command personnel to develop simplified communications characterization algorithms. Under the
auspices of the Technical Cooperation Program, Subgroup W Action Group 6 (TTCP
WAG-6), ACE researchers are working with United Kingdom researchers who have
developed the Computer Aided Staff Trainer (a voice communications command-post
simulator) to share knowledge gained in this common work area and to identify polential cooperative efforts for the future. Further ahead, a fire support control symposium may be co-sponsored with the Army Research Office to bring the best thinking
of the other services, industry, and universities to bear on fire support control problems.
In general, the planned order of ACE work will begin, as described above, with
the most basic fire support control ele1ments and continue with the building of higherlevel brigade-area elements. The first integrated ACE fire support control system will
include the following elements: FO DM1D, FIST D*ND, Battery Computer Systemn
(ECS), and weapon system interfaces as shown in Figure 14. This system will provide
a reserch tool to begin the study of battery-level technical fire direction issue areas,
140
such as on-board gunnery computers, and some maneuver company-level tactical fire
support control issues, such as fire support coordination versus primary FO roles for
the FIST chief. Once this first system is operating, the increasingly complex bn and
bde FSEs or operations centers must be added to the ACE simulator to address
higher-level tactical fire support control issues.
Concurrent with the running of ACE system exercises during the summer of '81,
another pre-HELBAT-8 effort, the subset evaluations, will begin (at the Human
Engineering Laboratory). In this effort candidate subsystems and interfaces will be
evaluated and further developed for integration into HELBAT 8, which is now
scheduled for the fall of '81. As of this writing candidate DARCOM, TRADOC, and
private company systems described below are being considered and in many cases are
already being tailored for inclusion in the HELBAT-8 exercise. These systems can be
grouped into three basic functional areas: target acquisition, fire support control in the
brigade area, and firing battery operations.
The HELBAT-8 target acquisition candidates are depicted in Figure 15. As in
previous HELBATs, dismounted platoon FOs will operate from terrain vantage points
with various laser range-finder (LRF) devices. These will probably include the
tripod-mounted Ground Laser Locator Designator (GLLD) and the Marine Corps
laser locator designator, the Modular Universal Laser Equipment (MULE), both with
automatic data links to the DMD and with developmental or experimental north-finder
modules for azimuth reference. Other prototype tripod-mounted LRFs and the soon-
to-be-fielded handheld LRF may also be included in the exercise for comparison. The
Interim FIST vehicle with a pintle-mounted GLLD (on a standard M113A1 APC) will
also be included as an acquisition device with a key issue being line-of-sight (LOS)
observation capability from positions accessible by the vehicle. To further address this
issue, an experimental telescoping mast-mounted target acquisition/designating system
(TADS) is being specifically modified.for inclusion. As requested in the HELBAT-8
priorities (Figure 10), airborne observers will also be included; some will be equipped
with stabilized TADS if available. Under the auspices of JTCP VWAG-6, the participation of a tethered observation platform was discussed with a Canadian company, but
because of scheduling problems, will not be available in the HELBAT-8 time frame.
An experimental computer-based radar netting system was demonstrated at Ft.
Sill during early FY 81. This system was capable of automatically analyzing and
integrating target intelligence data, from Firefinder (counterfire) radars and groundbased and airborne moving target indicators (MTI) radars, to form confirmed target
data lists. Although this system does not (at this time at least) integrate all the
brigade-area target acquisition systems, it is an existing hardware concept that could be
used to investigate the full brigade-area target integration center (ETC) concept in
HELBAT 8 and wveas therefore pursued as a candidate for the exercise. Because of the
prohibitive costs involved, this system -will not be available for HELBAT 8; however,
tactical scenario-related data message loads may be developed for more fully exercising
bde and bn FSEs. This could be acromplished by inserting time-ordered messages
into the data communications system using standard DMDs.
141
New concept fire support control candidates for HELBAT 8 are depicted in Figure
16. Target acquisition elements such as pit FOs and the FIST HQ wvill be interfaced to
the fire support control system through "super" DMDs that will be especially modified
for HELBAT 8 to permit alternative operation on wire line, standard push-to-talk
radios, or automatic data distribution system (ADDS) radios. These super DMDs will
also incorporate the HELBAT-7 modifications, automatic polar-to-grid conversion and
time-tag capability, and will be used by the other target acquisition candidates for data
communications with one or more (multiple addressees) of the decision nodes in the
brigade-area fire support control system (FIST HQ, bn FSE, bde FSE, btry or bn
FDC), depending on the type mission that is being conducted at the time. Experimental commercial-hardware Packet (ADDS) radios, which will be mounted in
environmentally controlled cases for ruggedization in the HELBAT field exercise, will
be the primary communications means in the brigade-area system depicted in Figure
16. Although the Packet radios are not yet militarized and may not be the first ADDS
radios to be fielded, in the HELBAT-8 time frame they are the only ADDS radios
available to demonstrate dedicated high-technology data communication - the crucial
key to reliable and responsive data-world fire support control and more specifically
here, to the successful operation of the new-concept HELBAT-8 brigade-area system.
For the first time in any IHELBAT exercise, the full fire support control spectrum
will be p!ayed: fire support planning, fire support coordination, and tactical and technical fire direction. As shown in Figure 16, the players include both a bn and a br1
FSE, a btry and a bn FDC, and technical fire direction on the guns. In the HELBAT
exercise, both the bn and bde FSEs will be equipped with (industry-conceived) experimental smart, (flat-panel display) graphics terminals that will be programmed to
automatically perform some fire support planning and coordination functions and will
automatically monitor and display (with military symbols) standard TACFIRE messages. A standard TACI1RE battalion computer center will be included as the bn
FDC and it, like the other players, will be able to alternatively operate on the ADDS
radios as well as on standard push-to-talk radios. At the btry FDC, graphics peripherals in the form of a printer and a plotter will be added to the FDC computer, and
new softrare will be developed and used to permit the evaluation of limited tactical
fire direction at the battery level. An existing experimental digitized terrain analysis
system may also be interfaced to the battery FDC computer. The btry FDC will be
set-up and operated in a tracked vehicle with active NBC protection. This vehicle will
be based on the armored ammunition resupply vehicle (ARV) concept that was fabricated on a. M109 howitzer chassis for HELBAT-7; the use of an ARV vehicle will
afford the FDC a nonunique signature in the battery area.
The weapon systems, which will be included in the new concept brigade-area
firing blattery, are described in detail in Figure 17. Building on lessons learned with
Howitzer Test Beds (HYBs) 1 and 2 in IHWIBAT 7, HTB 3 and 4 are currently being
designed and fabricated as follow-on efforts. Both new howitzers will incorporate
ADDS radio automatic data links, on-board technical fire direction computers, gyro
systems for local self-survey and pointing reference, and gunner display units (GDUs)
and chie.f-of-sectjon display units (CSUs). Hf-1B 3 will be a fully integrated systlmn
using a gimlbatled gyro sysLem and servos to permit even automatic laying (aiming) of
142
the gun tube, while HTB 4 will incorporate hardware that has been developed for
other applications. HTB 4 will utilize (trunnion mounted) strapdown gyro hardware
that was developed for the Advanced Attack Helicopter and the FIST DMD hardware
reprogrammed to perform modified point-mass gunnery as well as the standard
TACFIRE data message terminal function. Both HTB 3 and 4 will use automatic feedback from ballistics and fire control error sensors to investigate methods of improving
predicted fire, and both will also be interfaced to the new prototype armored ARVs.
A wire-line or radio data link between the howitzer and the ARV will be used for
communications, and the ARV auxiliary power unit (APU) can supply electrical power
to the howitzer as a redundancy option.
A summary of the ACE-i and the HiELBAT-8 plans is depicted in Figure 18.
Note that a complete standard TACFIRE brigade-area system (including the Variable
Format Message Entry Device (VFMIIED) for the bn and bde FSEs) will be operated in
HELBAT 8 to collect common baseline data against which the performance of the new
concept brigade-area can be compared. Both the bde FSE and bn FDC will alternatively serve as standard and new-concept elements. Although the FIST chief and bn
FSO may be separated from their respective HQs or element, this communications
complication will not be played as indicated by Xs. Although not discussed above, the
following equipment will also be included in HELBAT 8: Marine Corps Digital Communication Terminals (DOTs, a digital data terminal with graphics) and Mortar Fire
Control Calculators (MFCC, a data-communications mortar gunnery computer). The
Fie'd Artillery M\Veteorological Acquisition System (FAMAS, a developmental system
that can automatically update ballistics met in TACTIRE) was pursued for inclusion in
HEiBAT 8, but could not bs made available; met, however, will be provided via data
communications (from a V.EMED) for HELBAT 8. Under the auspices of TIfCP
WAG-6, various international hardware candidates for H-ELBAT 8 were discussed, but
for various reasons, none could be made available; however, UK representatives will
participate in the exercise and a CA officer will work with the HELBAT Working
Group from May until December 1981.
143
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Bibliography
1. Oerations, Department of Army (DA) Field Manual (FM) 100-5, 1 July 1976.
2. Fire Support in Combined Arms Operations. DA FM 6-20, 30 Sept 1977.
3. Field Artillery Cannon Gunnery. DA FM 6-40, ~Nov 1978.
4. "Close Support Study Group 11 (CSSG 11) Final Report," US Army Field Artillety School ACN
57393, 1 Feb 1980.
5. Field Artillery Cannon Gunnery, DA FM 6-40, 5 Oct 1967.
6. "Guide for Fire Direction Operations," US Army Field Artillery School (USAFAS) Gunnery Department, May 1978.
7. William J. Dousa, Jr. aod Cary L. Horley, "The Roles of Laser Syslems in Artillery Use" US Army
Human Engineering Laboratory (USAHEL) Technical Memorandum (TM) 9-78, Apr 1978, (Conf.).
8. William J. Dousa, Jr., "A Surmmary of Capabilities of Artillery For-ard Observers Equipped with
Laser Rangefinders," USAHEL TM 9-80, May 1980.
9. Tactical Fire Direction Svsiem. DA Training Circular (TC) 6-1, 15 July 1977.
10. "TACFIRE Reference No-e," US Army Field Artillery School Reference Noie (RN) FC--AA, Dec
1976.
11. Edward D. Ray, "TACFIRE - A Quantumrn Leap in FA Data Processing," Field Artillery Journal,
VoL 47, No. 3, May-Jun 1979.
12. Unpublished data from INLAJ L. Morris, TACFJIRE-TSM Office, USAFAS, 23 Apr 1980.
13. "User Ealuation of the Tactical Fire DLiection System AN/PSGIO (TACFIRE)," distribued by
USAFAS TACEIRE-TSM1 OErhe Letter of Transmittal, 2 Oct 1979.
162
14. Cannon-Lanched Guided Proictile Reaction Time VieTraph presented by Edwzrd Smauch, Army
Maleriel System Analysis Activity, at Third Artillery System Engineering Working Group In-Process
Review, 1 Aug 1979.
15. R. B. Pengelley, "HIE_13AT - The Way to Tomorrow's Artillery," Inlernational Derenrce Review,
Jan 1980.
16. Thomas E. Kinney, Jr. and Michael G. Golden, "HELBAT-7 Sublest - Ammunition Handling
Study", USAHEL TM 4-81, 1Mar 1981.
17. Michael G. Golden and Frank R. Paragallo, "HELBAT-7 Subtest - Howitzer Emplacement and Fie
Control Accuracy Study," USAHEL TM 15-80, Aug 1980.
18. Barry L. Reichard and LT Sam Chamberlain "FIST Vehicle and Associated Equipment - Preliminary Hardware Evaluation Comments," US Army Ballistic Research Laboratory Paper, Mar 1979.
19. "A Report on DRS," by LTC Homer J. Gibbs, Field Artillery Journal, Vol. 46, No. 3, May-Jun
1978.
20. "3x8 Direct Support Field Artillery Bantalion - Armored and Mechanized Infanury Division - Organization ard Operational Concept," US Army Field Artillery School Document, Apr 1980.
21. Discussion with MAJ David Scott, TACFIRE-TSM Office, USAFAS, 23 Apr 1980.
22. "Command and Control of Surface to Surface Artillery (1°86-2000)," USAFAS Draft Concept Paper, 25 Jun 80.
163
164
A
PRACTICAL APPLICATION
OF MAU IN
PROGRAM DEVELOPMENT
BY
Major James R. Hughes
United States Marine Corps
Concepts, Doctrine, and Studies
Development Center
22134
Quantico, Virginia
165
INTRODUCTION:
Recently, the Systems Analysis Branch at the Marine Corps Development
Center analyzed the Soviet threat employing the Multi-Attribute Utility Model.
The Soviet force consisted of a Motorized Rifle Division. The purpose of the
analysis was to identify the critical intelligence parameters required for
documentation to support acquisition of a Mobile Protected Weapons Systems
(MPWS).
The analysis enclosed herein includes:
o
Application of the Multi-Attribute Utility Model.
o
Identification of general attributes important to the success of the
MRD.
o
Utility curves (Appendix C).
o
Identification of attributes desired in the MPWS for countering the
identified threat.
166
METHODOLOGY:
The analysis applied the Multi-Attribute Utility Model to identify the
weapon systems/equipment which an MRD commander would emphasize during
Offensive Combat Operations.
The salient attributes were initially identified during a brainstorming
session. The group included intelligence experts from within the Marine Corps
Development Center.
In the application of the Multi-Attribute Utility Model, a problem is
decomposed into clearly defined components in which all options, outcomes,
values and possibilities are depicted. Quantification in the form of the value
for each possible outcome and the probability of those values being realized
can be in terms of objective information or in the form of quantitative
expressions of the subjective judgments of experts.
Beyond its primary role of serving as a method for the logical solution of
complex decision problems, multi-attribute utility analysis has additional
advantages as well. The formal structure of the analysis makes clear all the
elements, their relationships, and their associated weights that have been
considered in a decision problem. If only because the Multi-Attribute Utility
Model is explicit, it can serve an important role in facilitating communciation
among those involved in the decision process.
With a decision problem
structured in this type of analytic framework, it is an easy matter to identify
the location, extent and importance of any areas of disagreement, and to
determine whether such disagreements have any material impact on the indicated
decision. In addition, should there be any change in the circumstances bearing
upon a given decision problem, it is fairly straight-forward to reenter the
existing problem structure to change values or to add or remove problem
dimensions as required.
It should be emphasized that in no sense does this analytical approach
replace decision makers with arithmetic or change the role of wise human
judgment in decision making. Rather, it provides an orderly and more easily
understood structure that helps to aggregate the wisdom of experts on the many
167
topics that may be needed to make a decision and it supports the skilled
decision maker by providing him with logically sound techniques to support,
supplement and ensure the internal consistency of his/her judgments.
The complex decision problems confronted in any developmental program can
be difficult to resolve for a variety of reasons. Frequently, options are not
clearly defined, the results that might be achieved by opting for one choice
over another may be highly uncertain, and it is often difficult to determine
relative preferences for the possible decision outcomes. Certainly, almost
everyone has encountered decision problems characterized by such uncertainty.
Usually, the reaction is either to devote more thought to the circumstances
than would normally be afforded, or to resort to various devices to help sort
out the decision such as listing pros and cons for each option, rank ordering
preferences, listing the things that could go wrong, and so on. In either
case, whether through extended contemplation of the problem or through
recourse to more explicit written aids, the person with the problem, the
decision maker, attempts to lend structure to the problem to reduce it to a
more explicit tractible form. In a much more systematic and formal way, that
is exactly what multi-attribute utility analysis helps to do.
Initially, in this application, the breadth of the threat was deduced.
After extensive discussion the threat was conceptualized as follows:
take advantage of the availability of
sophisticated, highly-effective and highly mobile weaponry in all
levels of conflict.
adversaries
will
o
Potential
o
A common characteristic of all potential adversaries is their neartotal dependence upon the USSR for the material means of conducting
war.
o
As with
Soviet military doctrine, the principles of defense
against amphibious assault have as their goal, the creation of
conditions which will allow the Soviet commander to initiate decisive
action while denying the landing force commander the same capability.
In futherance of their goal, the Soviet defense is based upon highall
168
intensity mobile operations using large numbers of tanks and armored
fighting vehicles, extensive use of supporting arms and tactical
aviation, and echeloned, defense-in-depth deployed in an integrated
combined arms concept.
o
As an outgrowth of this concept of defense, certain Soviet weapons
systems will be of particular concern. The mobility, firepower, and
protection offered by tanks and armored fighting vehicles will afford
the Soviet commander a decided advantage against Marine landing forces
as they are presently equipped.
This capability will be greatly enhanced by the introduction of the T72 and T-80 series tanks, with their vastly improved armor protection,
power plants, armament and fire control systems. More than 200 such
tanks will be encountered in a representative motorized rifle
division, the primary tactical element against amphibious assault.
Infantry mobility and fighting capability will also increase with the
introduction of improved armored fighting vehicles of the BMP, BMD,
BTR family, more than 400 of which will be encountered in the motorized
rifle division.
o
In addition, infantry in prepared defensive fortifications, will also
confront both waterborne and helicopterborne assault elements.
o
The Soviet commander will also enjoy an increased capability to employ
air and artillery delivered ordnance against the landing force.
Tactical aviation will expand dramatically with the widespread use of
attack helicopters such as the HIP and HIND. Artillery will increase
both in numbers and mobility with the self-propelled 122mm and 152mm
gun/howitzer playing an expanded role.
169
The general conceptual attributes which contribute to the success of the MRD
are:
o
o
Offensive Combat Operation
Defensive Combat Operation
Although an MAUA was conducted for each only the former will be presented
here.
170
The MRD in Offensive Combat
The three types of offensive action are:
o
Meeting engagement
o
o
Breakthrough
Pursuit
Meeting engagement
The meeting engagement,
i.e., the collision of two opposing forces, is
stressed more in Soviet military writings than any other form of offensive
action. Because of the fluid nature of modern war, the Soviets believe that
the meeting engagement will occur more often than any other type of combat
action. Meeting engagements are characterized by action to sieze and maintain
the initiative; the development of combat on a wide front with freedom of
maneuver and the presence of open flanks; rapid deployment of troops, chiefly
from columns; mobile, high speed combat, and often incomplete intelligence on
enemy forces.
The Soviets believe that it is both possible and necessary to anticipate
meeting engagements; that through various intelligence gathering means they
will be prepared for and will aggressively seek out such engagements.
The Breakthrough
The classic breakthrough operation is a frontal assault against a wellprepared defensive position, using a large amount of artillery and maneuver
elements on a narrow front. The breakthough may also loccur against a hasty
defense. Against each type of defense, the Soviets envision a swift and deep
envelopment, the bypassing of stubborn pockets of resistance, decisive meeting
engagements with advancing enemy reserves, continuation of the attack, and the
subsequent destruction of enemy strong points by second echelon units.
Breakthroughs may be accomplished in short periods of time due to nuclear
strikes and the increased lethality of conventional weapons. Successfully
conducted meeting engagements and breakthroughs result in the pursuit and
ultimate destruction of the enemy's forces.
171
The Pursuit Operation
Pursuit operations are highly mobile in nature and are best conducted on a
wide front along parallel routes.
It involves both frontal attacks and
envelopment to cut off and destroy enemy forces. Pursuit operations are made
more effective by the use of tactical heliborne and airborne forces, which
occupy and defend locations in the enemy's rear and otherwise disorganize and
delay his retrograde movement. The Soviets stress that the pursuit is to begin
immediately upon the initiative of the commander who discovers the retreat.
"Maneuver" is defined in Soviet military literature as the movement of a
force into a favorable position in relation to the enemy, from which it can
launch an effective attack. The Soviets mention two basic forms of maneuver,
the frontal attack and the envelopment; but favor the latter which may be
shallow or deep, depending on the size of the unit executing it. Should the
enemy not have an assailable flank, a frontal attack would be used. A frontal
assault may occur on a wide or narrow front with or without heavy fire support.
Tank heavy second echelon forces attempt to exploit any rupture in the enemy
position. Under favorable conditions, however, the Soviets would attempt air
envelopment, possibly in conjunction with a frontal attack to pin down enemy
forces.
Envelopment is the preferred method of maneuver in the meeting
engagement and is used from platoon level up.
Accordingly, mobility, and those attributes which contribute to mobility
are heavily weighted in offensive operations. In fact, mobility composes .43%
of an MRDs offensive capability.
Conclusions
o
The MRD relies on speed and those attributes which contribute to speed.
o
The HIND, TANKS, BMP and self-propelled artillery are the greatest
contributing factors in the offensive capability of the MRD.
o
If concentrated efforts are made to constrain the speed with which an
MRD moves, maneuver and flexibility will also be affected.
172
Firepower in the Offense
Artillery fires in support of offensive operations are subdivided
three sequences or phases.
into
o
Preparation fires, centrally planned and executed are normally 30 to
60 minutes in duration and immediately precede the attack by motorized
rifle and tank forces.
The preparation includes conventional
artillery fires and air preparation and many include strikes of
rockets and missiles. The artillery preparation normally is initiated
with a powerful, surprise fire onslaught of all the artillery and
mortars against strong points in the main battle area and
simultaneously against U.S. artillery and mortars, dug in tanks and
antitank guided missiles, command posts, radars and reserve forces in
the immediate defensive positions. A second powerful fire onslaught,
with the main mass of fire concentrated on artillery and mortar
batteries, command posts and strongpoints, is timed to coinside with
the attack of the motorized rifle and tank forces.
o
Fires supporting the attack consist of scheduled and on-call fires in
support of the motorized rifle and tank forces. As attacking forces
near U.S. positions, the preparation fires are shifted, and fires in
support of the attack commences. Opposing force artillery doctrine
requires continuous support of the attacking force with artillery and
airstrikes, right up to the accomplishment of the combat mission. This
technique insures the constant neutralization or destruction of the
U.S. force by concentrated fire.
o
Fires through the depth of the U.S. defense are planned to give
uninterrupted fire support during the neutralization of successive and
final objection.
Displacements of artillery normally are required
during this sequence and are made so that not more than one-third of
the supporting artillery is out of action at any given time. When the
attacking motorized rifle and tank units have advanced so far as the
U.S. regimental/brigade reserve and main artillery positions, control
of artillery is decentralized and the artillery groups revert to the
control of the supported regiment or division commanders.
173
Conclusions:
o
Firepower is the key to successfully conducting offensive operations
employing an MRD.
o
The Tanks, BMP, HIP and HIND and self-propelled artillery provide the
bulk of the MRDs firepower capability.
o
Firepower in the offense contributes .48% of the total combat power of
the MRD.
o
Priority of targeting should go to the self-propelled artillery and
aviation in order to denude the BMP and TANK of their supporting fires.
In conclusion, the MAUA provides an effective method for evaluating the
deficiencies of a systems mix in relation to the threat. As a result, by
conducting the MAUA, the requirements for the MPWS were more easily
recognizable.
Additionally, the specific attributes desired in the system
were more easily defined and placed in this proper relationship to one another.
The multi-attribute utility approach described herein has a number of
advantages. First, it permits an individual who is an expert in a particular
area of expertise to narrow his judgment, rather than making an overall
judgment of worth, which may fall outside his area of expertise.
Second,
disaggregating the judgments of individual experts provides an explicit trail
leading from measures of system performance to measures of benefit or utility.
The judgments are public rather than private and are subjected to screening.
Appendix (C) demonstrates the same resultant utility curves from the MAUA
conducted in conjunction with the threat assessment for the MPWS. These curves
demonstrate some of the attributes desired in an MPWS. It should be noted that
C3 was not considered to be an important attribute because of the fast moving
environment within which MPWS will function. By the time the enemy knows where
you are, you are no longer there. Therefore, communication security plays a
smaller role.
174
APPENDICES
175
APPENDIX A
176
Important Attributes to be considered for MPWS as a result of the MAUA:
o
MPWS must be transportable by CH-53E helicopter.
o
MPWS must be strategically and tactically air transportable.
o
MPWS must have amphibious shipping compatibility.
o
MPWS must have a fording capability.
o
MPWS must have an NBC defense over-pressure capability.
o
MPWS must
be
capable
of
being
transported
behind enemy forward
elements in order to disrupt or delay attack of the second echelon of a
motorized rifle division.
o
MPWS must
be
capable of
providing forward,
rearward,
and flank
security for an armor equipped force.
o
MPWS must be capable of conducting advance force operations in order to
cause premature and misdirected commitments of enemy main forces
and/or to disrupt/interdict enemy lines of communications, main supply
routes, and command and control facilities.
o
MPWS must be capable of providing assault support and anti-armor
protection to an infantry unit operating within an extended tactical
area of responsibility.
o
MPWS must contribute to speed mobility and flexibility.
177
APPENDIX B
178
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APPENDIX C
181
I. The following utility curves were developed subjectively using MAUA and
reflect the consensus of the
analytical community.
operational
community as
opposed to the
A. Firepower considerations include lethality, accuracy, target acquisition,
servicing rate and stowed kills.
(1) Lethality is measured in terms of probability of kill given a hit, or
P(K/H).
Lethality is considered against tanks, light armor, materiel,
personnel, and helicopters.
In all cases, this lethality can be
achieved with any weapon system on board the MPWS (gun, missile, or
other).
(a) Lethality Against Tanks - Considers the T72 tank as the worst case
target. A kill can be either a mobility or a firepower kill (M or
F kill)
which requires more than 24 hours to repair.
Probabilities
for
P(K/H)
assume
a cardioid
single shot or burst per trigger pull.
-
L t t
11-1
tI
X]t -
I I I II
1tllr
r /l
Y . _ __
_
Hi
Vs
lX I
182
_
I
and
2KM is the most likely
range, but better standoff is preferred (4KM).
terrain limited rather than vehicle limited.
UTILrT
distribution
At 4KM, P(K/H) is
(b) Lethality Against Light Armor - A high probability of kill given a
hit is important to eliminate the light armor threat.
This will
enable other antitank weapon systems to concentrate on tanks.
A
kill can be either a mobility or a firepower kill (M or F kill)
which requires more than 24 hours to repair.
BMP is the expected
target; cardioid distribution is used; BMP threat is severe at
2KM and more limited at 4KM; therefore, the curve for 2KM rises
very steeply at higher probabilities.
MPWS must achieve P(K/H)
of .4 at 2KM, .2 at 3KM, and :1 at 4KM or it has little value.
s
! J I 1} I ) ] j i t
_ _ _~J
~j
] _ ] ]t _ _ I 1
It _ _t_
1t
X
X
I
'! r13t
3 -A
133
I
I
I
l
I
MC
Lethality Against Materiel Targets - Materiel targets can include
8" reinforced (horizontal and vertical) concrete at 3000PSI
strength; 16' x 12' wall; bunkers can include 6" x 6" bolted; 2'
sand on roof; 4' enclosure; 7' sand (outside to 1st timber); 18"
bunker and sand above ground. Bunkers and bunker type targets are
important in infantry support in places in which tanks have
difficulty trafficking (for safety or other reasons, such as
MOBA).
Bunkers are the most demanding target in MOBA.
The
utility is a function of percent of basic load required to achieve
a catastrophic kill (render unusable) at 2KM. Utility drops very
rapidly if it takes more than 3% of the basic load, and not much
utility is gained if more than 10% is required. If the percent of
load is high, MPWS will need to resupply too frequently.
MO
:TR(IKI
) )
CA
I2.E
a 1-G...
} NL I I IIl)
I
II1
I]EN
t
Klt
I11
an
tl PC IC
tllt
lkSTLtY
ILL A M lIRIlt AP-El 51 2.tX
184
'
(d) Lethality
Against
Personnel
Targets
-
The
measure
of
effectiveness here is the ability to kill or suppress personnel
with a probability of .8 as a function of range. Most of the
benefit is gained at a range of 1000 to 1500 meters with 80% of
the utility achieved by 2000 meters.
I
:,
135
:j
cjjIj.
(e)
Stationary MPWS - Moving Target - A fixed range of 2000 meters was
used, and the target was assumed to move at 20KM/HR crossing speed
(12.4MPH). This parameter is an indicator of how well the fire
control plus main gun performs. There is no value if the MPWS
cannot achieve P(H) of at least .3.
II
EI I
.
[Tt
T_
2.
-1
.Q
_I
.2 .
1 .36
136
I
l .I
t
.
.
.7
i l -F
() Moving MPWS - Stationary Target - This assumes that MPWS is moving
at 20KM/HR., (12.4MPH), and line of sight is constant. A range of
2000M is assumed. A large increase in utility occurs if P(H) can
be pushed beyond .3.
r~ll,
187
(g) Accuracy of the Secondary Fire Control System - The utility curve
assumes line of sight, perfect environment, and a stationary
target at 2000 meters. The secondary system can be less accurate
than the primary system but still must achieve P(H) = .4 to have
any value.
FC"1d
- I
~f
rFXI*
I
1 Xo
|7
.4
.A
PaC
.X
.I
.1I
1.0
(h) Lethality Against Helicopters - The curves assume a hovering
helicopter has been acquired at 4000 meter standoff range, and
MPWS is stationary. Lethality includes kill or suppression. In
this case, probability of kill equals probability of hit. The
curve
starts to rise more rapidly if P(K) of at least .5 is
achieved.
O S·
I 11 1
1
-t i ..
r r X1 111
i-T-
~ ': -- :
o
.1
.2
.3
I iI tI
t II I , j i
-i
/
~ i
.it
--'"T]
r~ _
t t
tJ_
.4
189
.s
.t
.7
.I
.!
1.0
190
HIERARCHICAL VALUE ASSESSMENT
IN A TASK
FORCE
DECISION ENVIRONMENT
BY
Ami Arbel
Advanced Information & Decision Systems
201 San Antonio CirclZe, Suite 286
Mountain View, California 94040
191
Hierarchical Value Assessment
in a Task Force Decision Environment
By
Ami Arbel
Advance-d Information & Decision Systems
201 San Antonio Circle, Suite 286
Mountain View, California 94040
ABSTRACT
This paper presents a new approach towards the derivation of a value
function to be used in decision problems faced by the CTF and his staff.
This
value function is task-dependent and may vary from one decision environment to
another.
This specifity is what distinguishes this approach from others where
*the value function is developed external to the decision problem.
192
1.
INTRODUCTION.
Decision problems at the task force commander (CTF) level involve
issues that are complex and, at times, critical.
This complexity together
with complicating factors such as time pressure and stress associated with
this decision environment may degrade the quality of the decision process
itself.
This general background motivates the effort directed toward develop.
ing decision aids for the CTF and his staff.
Decision'aids developed thus far resulted in models describing recurring situations such as emission control and transit planning, as well as
structuring aids for general decision problems.
The problems considered in the
second class are those that can be addressed and solved through a decision tree
formulation.
Such decision problems are solved after developing the structure
appropriate to the problem itself.
tification of
cause
This structure starts with a general iden-
and effect (influence diagrams) which leads to a decision
tree description.
Next, probabilities have to be assessed for the various
events described.
Last, by assigning certain values to anticipated events, a
preferred course of action can be prescribed.
The question of "value" is addressed through the concept of utility.
This
results in a number being assigned to outcomes that permits their evaluation.
This utility function is assessed by' talking with the CTF and members of his
staff, and used as a true representative of their choice-making attitude, whenever a choice has to be made in the decision process.
This utility, or value
function, is supplied as input to the process and used in various decision problems.
In considering various decision making scenarios it is easy to see the
deficiencies
of
decision problem.
this approach of supplying a value function external to the
As an example, consider the value associated with two types
of airplanes, say an F-14 and an A-7.
One may be tempted to compare firepower,
speed, and general sophistication and conclude that the F-14 is, say, four
times as valuable as the A-7.
While this conclusion may hold true in most
193
situations, it should not be accepted as the universal value assessment.
This
is so because there may be certain missions (e.g., tactical air strikes) for
which the A-7 will be far more valuable than the F-14.
This paper presents an approach towards value assessment in the
task force decision environment.
The approach organizes the value problem
into an hierarchy that considers all the factors that are relevent to the
value question.
The end result of this hierarchical value assessment approach
is a task-dependent value function (rather than an external input).
The structure of this paper is as follows.
general task force decision evnironment.
foundations of the approach.
Section 2 considers the
Section 3 presents the analytical
Section 4 presents the specific steps involved
in establishing a value function, and Section 5 presents a summary.
2.
A TASK FORCE DECISION ENVIRONMENT
The Naval task force decision environment described in reference
[1] highlights the fact that decision processes followed by task force
commanders vary from one CTF to another.
In very simple decision problems
the decision may just be a snap judgement with no structured process (even
though it obviously draws on the CTF's past experience).
In other simple,
yet routine, decision problems an old operational order can be used as a
guideline in drafting a new one to meet the particular situation at hand.
General guidelines for decision making in more complex situations are offered in various naval publications.
194
In complex, nonroutine, decision situations the approaches mentioned
above cannot be relied upon in formulating a course of action.
Even the avail-
ability of naval publications like NWP-11,and others, cannot be relied upon as
a sole source of aid in these complex situations.
simple.
The reasons for this are
When under time pressure it is likely to ignore some factors or options
and settle on a picture of a limited scope (optimizing vs. satisficing).
Also,
in these cases we have what is known as "judgement by availability" [2].
When
under time pressure and in a generally stressful environment decison making and
judgement ability will be greatly degraded.
vation for
These factors are the general moti-
developing operational decision aids to be used by the CTF and his
staff in these situations.
The main responsibility of the CTF is in formulating and executing a plan
of action called upon to
meet a certain perceived situation.
This decision
environment is described in Figure 2.1.
The decision aid depicted in Figure 2.1 interacts with the CTF and members
of his staff to elicit inputs that will allow the formulation of a plan which
is the end product of this particular decision process.
The basic elements'of
this process are discussed below.
The perceived mission and its environment (time pressure, criticality,
past experience, etc.) are major factors affecting the decision and judgement
qualities of the CTF and his staff.
This particular block is drawn in broken
lines in Figure 2.1 to indicate that it is not an explicit element of the process but it does contribute to the overall quality (or lack) of the decision
process.
The interaction between the decision aid and the CTF and his staff is
done as follows.
The CTF defines the general decision problem to be considered
(choice among options, priority assessment, planning, resource allocation, etc.).
The decision aid, through prompts and queries,
elicits various inputs from the
CTF and his staff in the form of requests for judgement.
ies
in
The prompts and quer-
a well designed aid, will follow a logical sequence that is particular
to the decision problem stated initially by the CTF.
For example, in the case
of a choice among options, one may be interested in developing a decision tree
description of the system.
ies
The decision aid should follow a sequence of quer-
directed toward eliciting, in an interactive step-by-step manner, the
particular structure as envisioned by the CTF.
195
Attempts toward this kind of com-
PERCEIVED MISSION
AND ITS
ENVIRONMENT
' \
\
/
/
CTF
AND
STAFF
Ctel
196
PLAN
puter aided structuring of decision problems have been reported in [3] and [4].
The result
of
the effort in this stage is a "model" that attempts to describe
the situation faced by the CTF.
The particular model developed may vary, and
may include submodels such as decision trees, strike outcome calculator, EMCON,
etc.
The development of a model, detailed as it may be, does not lead immediately to a plan of action. The reason for this is because the situations described
in the model are evaluated according to some value scale.
Utility theory was
developed and successfully applied in many decision problems.
Military situa-
tions offer a class of problems where a value scale (i.e., a utility function)
cannot be developed "off-line" in a manner disjoint from the problem under consideration. For example, in considering short-range operations (e.g., defense
of main body of task force) an F-14 may prove to be of much higher value than
an A-7.
In contrast, in considering an air strike this value assessment may
reverse itself.
This simple example demonstrates the need for a value model
to be used in conjunction with the model in deriving the plan of action.
The plan of action which is the end product of this process is directed
toward solving the problem faced by the CTF.
Specifically, this may include
types and sequences of military actions, force compositions, and resource allocation (e.g., equipment, personnel, supplies, etc.).
The approach taken here toward the development of a value model is
through the development of hierarchical value assessment schemes that are taskoriented.
The value model can then be incorporated into, for example, a de-
cision structuring process (such as reported in [4]) to yield an integrated,
robust, decision aid.
The technical foundations of the proposed approach are detailed in the
next section.
197
3.
HIERARCHICAL PRIORITY ASSESSMENT
The hierarchical value assessment scheme presented here is based on
Saaty's approach to hierarchical decision problems [5].
The basics of this
approach will be reviewed here and will be used in a naval decision problem
in the next section.
The Analytic Hierarchy Process is an approach recently introduced by
Saaty [5].
In this approach, the decision problem is decomposed into levels
containing objects with similar attributes (e.g., a level describing objectives and a level describing policies designed to meet these objectives).
The
approach is directed toward assigning priorities for each member in a particular level.
In particular, one is interested in ways to propagate the prior-
ities of each level throughout the hierarchy to establish priorities in a particular level of interest.
Consider, for example, the situation described in Figure 3.1.
GOAL
LEVEL I: OVERALL GOAL
LEVEL II:
OBJECTIVES
OBJECTIVE #1
LEVEL III:
POLICJES.
POLICY #1
Figure 3.1
OBJECTIVE #2
POLICY #2
Hierarchical Policy Evaluation
198
'POLICY #3
The decision maker has to evaluate the relative importance (priorities) of the 3 policies under consideration; this, in turn, will help
him later on in allocating resources to implement these policies.
The
policies themselves are designed to meet certain objectives (2 in this
particular case) that contribute to the overall goal the decision maker is
trying to attain.
In constructing hierarchical structures other than the one shown in
Figure 3.1, the following guidelines should be remembered:
1.
The number of levels used in a particular hierarchy
is not fixed and should be chosen to reflect the
particular problem at hand.
2.
The order of the levels should be one that reflects
a logical causal relationship between adjacent levels.
3.
The number of members in a particular level should be
chosen to describe the level in adequate detail.
The points mentioned above indicate that the construction of a particular hierarchy is not a process that follows-rigid rules but rather adapts
itself to the situation at hand.
Deriving the actual priorities of members in each level is done through
a pairwise comparison between each member of the level, relative to a member
of the adjacent upper level.
Let-us start the technical discussion by demonstrating the derivation of
priorities among a set of activities.
For illustration purposes, let us con-
sider 3 activities denoted by Ai , i-1, 2, 3.
We will compare the contribution
This
of these activities to a certain objective.
comparison will be carried
out pairwise and the result of the comparison will yield the relative weight,
This pairwise comparison can be
wi, of the activities under consideration.
summarized in a comparison matrix A given by
199
A =
Wl/wl
Wl/w 2
Wl/w3
W
2 /wl
W2/w2
W2/w3
W 3 /wl
W3/w2
W3/w3
(3.1)
The information displayed in this matrix is interpreted as follows:
every element, aij, of the matrix A shows the relative contribution to the
objective of the i-th activity compared to the j-th activity, i.e.,
a
A 'i
l<i<n,
l<j<n,
(3.2)
Wij
wj
This definition indicates that
1
aij
(3.3)
aji
which results in the matrix A being a reciprocal matrix; note also that the
diagonal of the matrix A in (3.1.) is l's.
Going back, for a moment, to Figure 3.1, one can construct a comparison
matrix that shows how each of the 3 policies contribute, say, to objective #1.
Every element of this matrix can be obtained from this line of 'questioning:
"Consider, for example, policy #1.and policy #2; which
· one contributes more toward objective #1 and what is
the strength of this contribution?"
Whenever the ij-th element of the matrix is filled out, the ji-th position
is automatically filled out by its reciprocal value.
To actually recover the weights, wi, themselves rather than their ratios
that are given in (3.1) we proceed as follows.
Note that
Aw - nw
(3.4)
Hence, a comparison matrix as given in (3.1) has (n-l) of its eigenvalues at
the origin and the n-th eigenvalue is equal to the dimension of the matrix A,
i.e., the number of activities compared (3 in our example).
200
Since
-n is the largest eigenvalue, we conclude that the vector of
priorities, w, is obtained from (3.4) and is simply given as the eigenvector
of the matrix A corresponding to the largest eigenvalue X =n. Since we
max
are interested in a relative ordering, this eigenvector is normalized so that
its components sum up to one.
There are 2 questions to be asked at this point:
1.
How does one quantify his judgement as to the
"strength of contribution" of a certain activity?
2.
How does one define consistency in this judgement
elicitation process?
These questions will be discussed briefly in the remainder of this
section.
The comparison process elicits qualitative judgemental statements that
indicate the strength of the decision makers preference in the particular comparison made.
In order to translate these qualitative statements into numbers
to be manipulated to establish the required priorities, a reliable scale has
to be established.
Much work has been done on the subject of scales in pre-
ference statements (see, e.g., [5], and the references therein), we will
not repeat here the arguments that lead to the employment of a particular scale;
instead, we will present a scale reported in [5] that we find to be useful for
our purpose.
This scale is shown in table 3.1.
When using this scale, one replaces a qualitative comparison statement
with the appropriate quantifier.
For example, if policy #1 is weakly pre-
ferred to policy #2 as fat as achieving objective #1, then a12=3 (and by reciprocity a 2=1/3).
1
Performing the complete pairwise comparison of all 3
policies relative to achieving objective #1 will result in a 3x3 matrix whose
(normalized)eigenvector yields the importance of the 3 policies relative to
objective #1.
In comparing activities, it is expected that if activity Al is preferred
to A 2, and A 2 is preferred to A 3 then Al should be preferred to A 3.
In employ-
ing a numerical scale one expects to see consistency maintained throughout the
comparison process.
Mathematically, consistency is defined as
201
Table 3.1
Comparison Scale
Intensity of
Importance
Definition
Explanation
1
Equal importance
Two activities contribute
equally to the objective
3
Weak importance of
one.over another
Experience and judgement
slightly favor one activity
over another
5
Essential or strong
importance
Experience and judgement
strongly favor one activity
over another
7
Very strong or demonstrated importance
An activity is favored very
strongly over another; its
dominance demonstrated in
practice
9
Absolute importance
The evidence favoring one
activity over another is of
the highest possible order
of affirmation
2,4,6,8
Intermediate values
between adjacent scale
values
When compromise is needed
Reciprocals of above
nonzero
If activity i has one
of the above nonzero
numbers assigned to it
when compared with activity j, then j' has
the reciprocal value
when compared with i
A reasonable assumption
aij = aik a
Vi,j,k
1,2,....,n} {C
(3.5)
This definition is simple to understand when one recalls (3.2), namely
w
a ij = wji
then, if one has already established the relative strength of activity i.compared to the k-th, and the k-th compared to the j-th activity, then this should
also yield the comparison of the i-th to the j-th activity; namely
aik ak
A
i
Wk
j twj
wi A ai
(3.6)
wj
When the nxn matrix A in (3.1) is consistent its largest eigenvalue is
equal to its dimension, i.e., X
=n.
max
.
202
When the matrix A is not consistent, i.e., equation (3.5) does not
hold for some elements, one can show that the largest eigenvalue of A is always
greater than n, i.e.,
X
max
(3.7)
> n
And the priority vector is obtained by solving the following eigenvector problem
for w
Aw i
X
max
(3.8)
w
One can define a consistency index by
C.I =
nmax-n
n-1
(3.9)
in the consistent case, C.I = 0.
Further details of this subject can be found
in [5] and will not be repeated here.
4. VALUE ASSESSMENT
The approach described in the previous section for priority assessment
can be adapted to the problem of value assessment.
This is accomplished by
constructing an hierarchy that describes the various factors affecting the
task force mission goal. Typically, such an hierarchy will have various levels,
whose specific description is part of the value assessment process.
These
levels may include the following:
*
Task force mission goal (the apex of the hierarchy)
*
Scenarios
*
Major task force objectives
*
Evaluation yardsticks
*
Operational options
*
Components of value function.
This particular hierarcy is depicted in Figure 4.1.
The specific detail
associated with each level may be different from mission to mission which, in
turn, may result in a different prioritization of the elements.
The bottom
level of the hierarchy includes those elements whose relative importance the
CTF has to evaluate in certain situations.
203
SCENARIOS
MAJOR OBJECTIVES
EVALUATION YARDSTICKS
OPERATIONAL OPTIONS
COMPONENTS OF VALUE FUNCTION
Figure 4.1
Hierarchical Value Assessment
204
For example, in considering an air strike against some enemy land targets the CTG (through outcome strike calculators or judgement) may anticipate
The particular plan to be
certain losses in, say, F-14 and A-7 airplanes.
chosen and implemented will be the one that, in addition to achieving the
mission will also minimize the expected loss.
This last objective requires
the availability of a value scale that will allow the relative importance of
the F-14 or A-7 relative to the overall task force mission goal.
A form of
a value function to be considered is a lineart relation given by
n
V =w
x w+ x2
2
Wi=l
+...+wnxn
x
(4.1)
i=1
where
Wi
relative importance of i-th value component
=
Xi - i-th value component.
In the particular example mentioned above, this value function may look
like
v = -w
1
(4.2)
x1 - w 2 x 2
where
xl - number of expected F-14 losses
X2
number of expected A-7 losses
w 1, w2
=
relative importance of F-14 and A-7
In a particular situation the CTF may consider the F-14 three times more
important to.his overall mission than the A-7; this will result in his value
function having the form
V
-0.75x 1 -0.25x 1
(4.3)
Then, whenever the particular loss assessment is supplied (i.e., values for
x1 and x2 ) one has a particular value number associated with-the specific situation being evaluated.
Other forms may also be considered, see, e.g., [6].
205
The value assessment method to be developed here is directed toward
obtaining the weights, wi, associated with the components of the value function
described in (4.1).
These weights are going to be the priorities associated
with the elements of the bottom level of the hierarchy described in Figure 4.1.
The specific levels described in Figure 4.1 may have different members,
in different situations.
An aid in specifying these levels may be provided
through a "Value Component Template" 'such as the one described in Table 4.1.
The list of items considered in each category should not be taken to beall-inclusive.
This list may be offered to the CTF and his staff as a suggestion for consideration.
They may check off those items found relevant to the particular situa-
tion at hand and, when necessary, may include other elements worth considering.
After checking off those elements relevant to the specific problem at
hand, one may arrive at the value hierarchy described in Figure 4.2.
The end
result of this analysis will be the relative importance associated with the
components of the value function; in the case of Figure 4.2, these components
include F-14, A-7-, DDG and a CV.
The knowledge gleaned from this process can
then be used in assessing various courses of action.
5. SUMMARY
This paper presented a new approach towards the derivation of a value
function to be used in decision problems faced by the CTF and his staff.. This
value function is task-dependent and may vary from one decision environment to
another.
This specifity is what distinguishes this approach from others where
the value function is developed external to the decision problem.
The actual derivation of the value function is through an hierarchical
value assessment that allows the consideration of all factors relevant to the
value issue.
This process, in addition to structuring the value function, also
indicates priorities associated with various factors.
These priorities assoc-
iated with intermediate level are useful in their own right.
They can be used
in the planning' stage to identify factors most important to the task force
mission goal.
206
Table 4.1
c,
Value Components Template (Preliminary)
*
POLITICAL CONDITION
_
PHYSICAL ENVIRONMENT
0
OPERATIONS
o
ILl
w
Co
o
o
·
-
0
SURVIVAL
WI
<
2 -~ : ·
TRAINING/READINESS
0
c
z
I----
I MORALE
LIVES
-0
*
EQUIPMENT
I
TIME SCHEDULE
'PEER EVALUATION
M cn
AIR STRIKE
*
SHOW OF FLAG
*
NAVAL BLOCKADE
S
SPECIAL FORCES
*
AMPHIBIOUS
*
INTELLIGENCE
$
TYPES OF AIRPLANES
*
SPECIAL EQUIPMENT
I
TYPES OF SHIPS
I
PERSONNEL
-J
z
co
o 0z
WI
wo
0
0
Zu
0
un
·
Z =
W L.
z
U
207
-v~~~~~~~~~~~~,-4
O
o
o
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0
I
o
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REFERENCES
1.
J.R. Payne, et al, "The Naval Task Force Decision Environment",
Final Report NWRC-TR-8, Stanford Research Institute, Sept. 1977.
2.
P. Slovic, B. Fischoff and S. Lichtenstein, "Behavioral Decision
Theory", Ann. Review of Psychology, Vol. 38, 1977, pp. 1-39.
3.
A. Leal, "An Interactive Program for Conversational Elicitation
of Decision Structures", Ph.D. dissertation, UCLA, 1976.
4.
M.W. Merkhofer, et al, "A Computer-Aided Decision Structuring
Process", Final Report, SRI International, June 1979.
5.
T.L. Saaty, "A Scaling Method for Priorities in Hierarchical
Structures", Journal of Mathematical Psychology, Vol. 15, No. 3,
June 1977, pp. 234-281.
6.
R.L. Keeney and H. Raiffa, Decision with Multiple Objectives,
John Wiley, 1976.
209
210
OVER-THE-HORIZON,
AND TARGETING
DETECTION,
CLASSIFICATION
(OTH/DC&T) SYSTEMS
SELECTION USING FUNCTIONAL FLOW
CONCEPT
DIAGRAMS
BY
Glenn E. MitzeZ
The Johns Hopkins University
The Applied Physics Laboratory
Johns Hopkins Road
Laurel, MaryZand 20810
This work was supported by the Naval EZectronics Systems Command
under Task ZN90 of Contract N00024-78-C-5384 with the Department
of the Navy.
211
OTH/DC&T SYSTEM CONCEPT SELECTION
USING FUNCTIONAL FLOW DIAGRAMS
ABSTRACT - In comparing various conceptual. configurations for the U.S.
Navy's future over-the-horizon/detection, classification, and targeting
(OTH/DC&T) system, we have taken a new look at some old techniques in
graphical analyses. The responsiveness of various candidate concepts was
Functional flow diagrams are
measured by (so-named) functional flow diagrams.
a slight adaptation and simplification of the diagrams used in the Graphical
Functional flow diagrams depict the
Evaluation and Review Technique (GERT).
By assigning a
sequence of functions required to perform an overall task.
probability of completion and distribution of time for completion to each
function in the diagram, the overall probability of completion is obtained.
In the
We review Monte Carlo methods for obtaining-the overall results°
process, we present some new results for confidence intervals on the probability
of completion versus time. The techniques have broad applicability to analysis
of any system concept where the time-sensitive probability of completing a
The techniques are especially useful for
well-defined task is of interest.
performing system tradeoffs and comparisons at a highly macroscopic level.
We apply the analysis techniques to compare "centralized" and "decentralized'
OTH/DC&T system concepts. The concepts are compared in four ways by taking
combinations of the OTH/DC&T mission to missile launch only or to recognized
enemy neutralization and simulations where hardware elements of the OTH/DC&T
system were either "perfect" or "realistic." The decentralized concepts were
better in all comparisons, except the "perfect" system in mission to launch
only where the concepts were indistinguishable.
1.
INTRODUCTION
Military, government, and industrial planners are often faced with the
problem of choosing among several proposed system concepts to solve a particular
problem. Time and resources often will not allow a detailed analysis, let
alone construction of system prototypes of each concept, so decisions must be
made on the basis of techniques applicable at a much higher level. Such is
the case with the design of an over-the-horizon/detection, classification, and
targeting (OTH/DC&T) system that satisfies the U.S. Navy's need for a worldwide
communications and data processing system to support weapon firing from ships
against targets beyond the range of on-board sensors.
212
Quantitative analysis of candidate OTH/DC&T system.concepts has relied
on a representation of the response of the system to new potential threats
in terms of so-called "functional flow diagrams" that depict the targeting
Use of these diagrams is
functions and the sequence in which they occur.
similar to the Program Evaluation and Review Technique (PERT) developed by
the Navy's Special Projects Office in the late 1950's and the Graphical
Evaluation and Review Technique (GERT), a refinement of PERT developed in
the mid-1960's [1].
Functional flow diagrams have been drawn to depict the
performance of various candidate OTH/DC&T system concepts in a selected
scenario. By making appropriate assignments of the probability of completion
and the distribution of time for completion to individual boxes in the
functional flow diagrams, the probability of overall mission completion
This has provided the basis
versus time has been computed in each case.
for quantitative comparison of candidate concepts.
Section 3
Section 2 defines functional flow diagrams explicitly.
overall-system
performance
Monte
Carlo
techniques
for
estimating
discusses
and presents some original work on confidence intervals for the overall
Section 4 shows the comparison
probability of task completion versus time.
of a "centralized" versus a "distributed" OTH/DC&T system concept using
functional flow diagrams.
2.
FUNCTIONAL FLOW DIAGRAMS
Functional flow diagrams are simple representations of the sequence of
The diagrams consist of
functions required to perform some overall task.
two types of boxes:
a.
Functional boxes, and
b.
Branching boxes;
and three types of connectors:
a.
AND,
b.
OR, and
c.
EXOR.
Each functional box (drawn as a rectangle) is characterized mathematically
in two ways:
a.
The probability of eventual completion, and
b.
The cumulative distribution function (cdf) or,
equivalently, the probability density function
(pdf) of completion time (given completion).
213
The input line to each box indicates the function(s) that must be
complete before the function can be initiated. An output line from each box
indicates the function(s) that can be initiated only after completion of the
function denoted by the box.
Each branching box (drawn as a diamond) indicates a decision that
influences the subsequent functional flow. The questions in the decision
boxes are stated in such a way that they an be answered Yes or No. The
branching boxes are, therefore, characterized in one way: the probability of
Yes branching or of No branching. Each connector box is represented by a
circle, and it has two inputs and one output line. The AND connector indicates
that all operations from both input lines must be complete before initiating
operations on the output line. The OR connector indicates that the completion
of either operation from the input lines is sufficient to initiate operations
on the output line. The EXOR connector is the same as the OR except that
only one of the input lines is active at any given moment due to earlier
branching decisions.
In addition, boxes must be included in the diagram to indicate the start
and finish of the overall task. A sample diagram depicting a simple generalized
task of neutralizing a target using the OTH/DC&T system is shown in Fig. 1.
The mathematical objective in drawing a functional flow diagramn is to
derive the time-dependent probability of completing the overall task which
the diagram represents, P(t),
from the characteristics of the constituent
boxes in the diagram. The time-dependent completion probability of overall
task completion by the time t (with the start of the first function in the
diagram defined as t = 0) can be written as
P(t) = p F(t)
,
(1)
where p is the probability of eventual completion of the overall task and
F(t) is the cdf of the overall completion time, given eventual completion.
3.
MONTE CARLO TECHNIQUES
The overall probability of completion and distribution of time for
completion of a task defined by a functional flow diagram can be computed by
analytical techniques [1,2].
However, often the diagrams are too complex to
conveniently manipulate the formulas or the data too scarce to support
identification of particular analytical forms for the completion time pdf's.
In the Monte Carlo technique, a large number of sample runs through the
diagram are made. As each functional box is encountered in the diagram,
random numbers are generated to decide (according to the assumed probability)
whether the function is completed and, if so, to add an appropriate delay
based on the assigned distribution of time to complete the function. At
branching boxes, a single random number is drawn to decide (according to the
assumed probability) which branch is to be taken. The results for all the
runs are accumulated and used to compute the fraction of successful overall
runs through the entire diagram and the histogram of completion times for the
successful runs.
214
START
(Acquisition of Initial Data)
RECOGNITION
CLASSIFICATION
LOCATI ON
CONTACT
EVALUATION
TRACKING
EANOD
iS
YES
ADDITIONAL
DATA
I\ENGAGEMENT
ANALYSIS
L
CU\
B NSOR
NO
[
EMPLOYMENT
AND
CONTROL
DAMAGE
ASSESSMENT
NO
YES
STOP
(Mission Complete)
Fig. 1
Generalized OTH/DC&T functional flow diagram.
215
From the results of the Monte Carlo runs, the probability of overall
task completion versus time P(t), as defined by Eq. 1, must be estimated.
The quantity on the left-hand side of Eq. 1 can be estimated by separately
estimating the overall probability of task completion, p, and the cumulative
distribution function of completion time (given completion), F(t), appearing
on the right-hand side of Eq. 1. The estimate of P(t) is then the product
of the two estimates,
(2)
P(t) = p F(t) ,
where p and F(t) are estimators for p and F(t), respectively, and P(t) is
If N Monte Carlo runs are made through the
the derived estimator for P(t).
diagram, success or failure in the completion of each run can be represented
by a binominally distributed random variable
=
(with probability p), if the ith run is completed
0 (with probability 1 - p), if the ith run is not completed
(i
=
-(3)
1,.....,N).
An estimator for overall probability of completion is
p= N
,(4)
a form that will be useful in deriving associated confidence intervals. If,
on any given set of N runs, exactly M successes occur, then there are M
samples of completion time that can be represented by
T. = completion time on jth completed run
(j = l,...,M)
(5)
An estimator for the cumulative distribution function is
(6)
F(t) = M(t)/M ,
where M(t) is the number of times T. does not exceed t.
Some assessment of the accuracy of these estimators is required as
The accuracy can be assessed in terms of
a function of sample size.
confidence intervals that encompass the actual quantities with a known
probability [3,4].
216
Confidence Interval on p
Confidence intervals for p are typically based on either the precise
binomial distribution of p (assuming independent runs) [5, pp. 273-285] or
on a Gaussian approximation of the distribution of p. The binomial approach
has the disadvantages that it is difficult to compute and gives little
insight into what sample sizes are required to achieve a desired accuracy in
the estimate of p.
The random variable
X
~(~p-
~p~)
/e
VP~~~
~(7)
(l~p^~)
converges (with increasing N in distribution) to a Gaussian random variable
with mean 0 and variance 1 [6, pp. 152-156].
This permits us to say that
the (random) interval
p
rN_
-P
,+/y
(8)
where C
is V
times the inverse error function (i.e., erf(Cy/i) = Y)
y
Y
contains the true parameter p with probability Y.
Because the true
parameter p must lie in the interval [0,1], the probability is also y
that the (random) interval
[max
(0,
P
_
m(1-))
(1
+
contains p.
The normality approximation is said [6, p.
values of N and p satisfying Np(l-p) > 20.
-
CY)
(9)
141] to be good for
Confidence Interval on F(t)
An exact confidence interval for F(t) can be computed by using the
distribution of the Kolmogorov statistic
DM = supfF(t) - F(t)
t
I
.
(10)
Kolmogorov [7] showed that the cumulative distribution function of D
does
not depend on the distribution F(t), which is unknown and assumed to be
continuous. The exact distribution of DM can be computed by assuming that
F(t) represents a random variable uniformly distributed between 0 and 1 [8].
Kolmogorov showed that for large M the distribution of DM tends toward
217
(-i
Prob{DM < x} =
)
exp(--2Mi 2 x2 ).
(11)
i=-O0
(Birnbaum [8) indicates that the agreement is good with M = 80.)
Sample values of hv x = x
of Eq. 11 can be found in [5, p. 440].
achieve a selected probability Y are as follows:
Y
Tabulations
required to
BY
0.80
1.07
0.90
1.22
0.99
1.63
(12)
Using these results, a 100y percent confidence interval for F(t) can be
computed, namely
[M)
-
X+/
F( )
.
X //
(13)
By Eqs. 10 and 11 the interval in Eq. 13 contains F(t), for all values of t,
with probability Y.
Since 0 -< F(t) < 1, for all t the interval
(max(O, F(t) - A /iM)
,
min(l, F(t)
+ X/
/i)]
has the exact same probability of containing F(t) for all values of t as
does the interval in Eq. 13.
Confidence Interval on P(t)
An exact confidence interval for P(t) is difficult to obtain, since
that would involve deriving the distribution of P(t) in Eq. 2. The
distribution of a product of random variables is in itself difficult,
but the distribution of F(t) is not even available.
However, it is possible
to derive an interval which contains P(t) with at least a specified
probability, from the confidence intervals for p and F(t) [9].
The
approach is to observe that if the event where p falls in the confidence
interval of Eq. 9 is independent of the event where F(t) falls in the
confidence interval of Eq. 14 for all vales of t (in the sample space
consisting of the Cartesian product of the two underlying sample spaces),
218
(14)
the probability of P(t) falling in the interval formed by multiplying
the lower and upper end points, respectively, of Eqs. 9 and 14 is at
least the product of the confidences associated with the individual
intervals. This is true because the event where P(t) falls in
max (O. p
min
-
£
)
max
E)
1l,
(0, F(t) - X/)
min
(1, F(t) -
(15)
(where a and B
contains the intersection of the two events described above
are the probabilities that p and F(t) are contained in their respective
confidence intervals). Therefore, the probability that P(t) falls in Eq. 15
It is clear that Eq. 15 could be used to generate many
is at least ac.
different intervals having the same minimum probability (i.e., ac) of
containing P(t) for all vales of t, by choosing various combinations of
a and ~ for which the product is fixed. It is interesting to ask whether
one of these choices results in a significantly more narrow interval than
others.
Optimal choices for a and B which minimize the maximum width of
the confidence interval are discussed in [9], and summarized below.
0.88600, 0.90297 for 80% confidence
a, ~=-0.94425, 0.95314 for 90% confidence
(0.99470, 0.99531 for 99% confidence
(16)
The maximum width of the confidence interval obtained by making these
choices will not exceed the bounds
I4.0404//i
for 80% confidence
4.6530/ViY for 90% confidence
6.2662//M for 99% confidence,
where M is the total number of completed runs.
219
(17)
As an example, Monte Carlo runs have been made through the sample
diagram shown in Fig. i. All functional boxes were assumed to have a
probability of completion of 0.95 and an exponential distribution of
completion time with mean 1.00, and all branching boxes were assumed to
have a probability of YES branching of 0.50.
When enough Monte Carlo
runs are made to obtain 10,000 completions, the probability of completion
is estimated to be
p = 10,000/25,268 - 0.39576 .
(18)
The associated 90% confidence interval as computed by Eq. 9 is
[0.39068, 0.40084]
,
(19)
which encompasses the analytically derived value of 0.3952.
The cdf as
estimated by Eq. 6 has an untruncated 90% confidence interval defined by
P(t) + 1.22//10,000 = F(t) + 0.01222.
A 90% confidence interval for P(t)
using Eq. 15 and choosing a and B according to Eq. 16 is given by
[0.38987 max (O,F(t) - 0.0137)
0.40165 min (l,F(t)
+ 0.0137)]
.
(20)
This confidence interval is plotted in Fig. 2 with a superimposed plot of the
analytical expression derived using the techniques described in references
[1] and [2].
The histogram of mission completion time is shown in Fig. 3
with a superimposed plot of the analytically derived pdf.
The pseudo-confidence interval on P(t), given by (15), is used in
[9] to address the important question of sample sizes required for selected
accuracies in the estimation of P(t).
To obtain estimates of P(t) via
Eq. 2 that are within p of the true value for all t, the required number
of completed runs is approximately
4.081.2/p 2
for 80% minimum confidence
5.4126/p 2 for 90% minimum confidence
9.8163/p2
for 99% minimum confidence .
220
(21)
0.5
0.4 -
so
i.
<
0.3
0
4,_
00.2
0
0. 1
Confidence interval
...._Analytical
expression
0
10
20
30
40
50
Time (arbitrary units)
Fig. 2
Confidence interval on probability of completion versus time from
Monte Cario runs (with superimposed plot of analytical expression).
221
60
Note:
bin width - 1.00
0.08
f.`.
o
-0_
1
1000
I
I
I
-I-
0.1
-800
total sample size = 10,000
g
6400
-
0
10
20
40
30
50
60
Time (arbitrary units)
Fig. 3
Histogram of completion time (with superimposed plot of analytical
pdf) for generalized OTH/DC&T functional flow diagram.
222
>
5.
COMPARISON OF OTH CONCEPTS
The above techniques have been applied to the evaluation of system
concepts of OTH weapon targeting.
The major problem to be solved by an OTH
targeting system is to acquire targeting data from several sensors that are
remote from the firing platform, to correlate targeting data from the several
sensors, and deliver that data to the firing platform on a timely basis.
The
two concepts of accomplishing this are characterized by the terms "fully
distributed" and "centralized."
In the fully distributed concept, contact data from each sensor are
distributed directly from the sensor to all system users, including firing
platforms. Upon receipt, the data are correlated, tracks are developed,
targets are identified from any background ships present, and a projected
target position is provided to the missile fire control system.
In the
centralized concept, contact data from sensors are delivered to a centralized
point in the targeting system. There, the data are correlated, tracks are
developed, targets and background are identified, and the correlated tracks
are then passed to the firing platform so as to develop a fire control
solution.
For each of the concepts, a functional flow diagram with assumred
performance characteristics for each function was developed [10].
The
results are shown in Fig. 4.
The diagrams were drawn to simulate a simple
scenario exercising several levels of command for both sensor and weapon
control. The diagrams can be found in [10] and contained about 200 boxes and
branches, as opposed to the 13 in Fig. 1, but generally followed the sequence
shown in the figure.
Two sets of performance characteristics were developed.
The first
corresponded to realistic performance.
The second set simulated perfect
performance of those elements of the overall mission which were performed by
OTH/DC&T system hardware (e.g., data processing).
Specifically, in the
second set of performance characteristics subfunctions not performed by
weapons, sensors, platforms, commanders and external communications were
assigned probability 1 of completion and zero time for completion.
This was
a means of exposing conceptual differences induced by entities more or less
outside the control of the OTH/DC&T system designer.
Two types of missions were considered.
The first included only the
launch of the first missile, corresponding to the "Weapons Employment" box in
Fig. 1, and stopped at that point.
The second included, beyond this, damage
assessment, and retargeting, if necessary, as many times as it took to
achieve a hit and correctly assess it as such.
With the two performance characteristics sets and two types of missions
there were four bases for comparing the systems concepts. Monte Carlo
results for all four are shown in Fig. 4.
223
/ ',// I '; ,
i/
100
,
.:......
90
E....
s
60
5o
1//
'
/
,
\50
0
40'
mO40!
~
20
C//j/L
~ ~~
~
~
Note: 90% confidence interval
'
P ~/
/
Fully distributed
--
/",/'J
:iiii!::?:i.
}
, //;
10
'/////7/
\\
/,,/'":':'"::.."-.
/
------\-Centralized
_
Mission to launch only, perfect system
* i:/X(two curves in distinguishable)
\:\.....,.. Mission to launch only, realistic system
/::¥:::::::::.Complete
/\\\\\\\\
0
. width
. :have
less than 0.04653
mission, perfect system
Complete mission, realistic system
X
0
250
500
750
1000
Time (arbitrary units)
Fig. 4
Comparison of time-dependent mission completion probability for fully
distributed versus centralized OTH/DC&T system concepts.
224
1250
In three of the four combinations (the perfect system to launch
only is the exception) the two concepts are clearly distinguishable.
The 90% confidence level intervals are not drawn but have width less
than 0.0465 and the difference in the curves for the two concepts are
typically much larger. Furthermore, the fully distributed concept is
superior in all three cases. We conclude from this that the "fully
distributed" concept should be selected over the centralized concept and
this conclusion is unaltered by the quality of performance of OTH/DC&T
system elements which are under the designers' control or by considering
damage assessment and retargeting functions beyond the initial firing of
an OTH weapon.
In the actual study, 26 candidate system concepts were identified
and compared [11].
The "fully distributed" and "centralized" concepts
discussed in this report are the two extremes in that set. When the
quantitative analyses were combined with qualitative analyses and operational
considerations which we have not discussed in this report, a modified
version of the "fully distributed" concept was selected.
6.
CONCLUSIONS
Functional flow diagrams provide a useful comparative system analysis
technique in those instances where timeliness and reliability are important
system considerations. The technique can provide some valuable insights
into system behavior. An interesting extension of this work would be to
cost-effectiveness analyses. Quite a bit of research in reliability has
been devoted to finding optimal distributions of available funds among
unreliable subsystems [12].
If the characteristics of the boxes in a
functional flow diagram are related to cost, the potential exists for
optimizing the completion probability curve (in some sense) over various
distributions of the total funds to the individual boxes. Another
extension would be in comparative analysis of enemy capabilities.
225
REFERENCES
1.
Gary E. Whitehouse, Systems Analysis and Design Using Network Techniques.
Englewood Cliffs, N. J.:
Prentice-Hall, Inc., 1973.
2.
G. E. Mitzel, "Documentation of Techniques for Evaluating Measures of
Value for OTH/DC&T Concepts," The Johns Hopkins University Applied
Physics Laboratory memorandum F4A-78-279, 18 August 1978.
3.
Richard M. Van Slyke, "Monte Carlo Methods and the PERT Problem,"
Operations Research, Vol. III, September 1963, pp. 839-860.
4.
P. J. Witzke, "Techniques for Statistical Analysis of Data Produced by
Monte Carlo Runs," The Johns Hopkins University Applied Physics
Laboratory memorandum F4A-79-128, 12 June 1979.
5.
D. B. Owen, Handbook of Statistical Tables.
Wesley, 1962.
6.
George G. Roussas, A First Course in Mathematical Statistics. Reading,
Mass.:
Addison-Wesley, 1973.
7.
A. Kolmogorov, "Sulla determinazione empirica di una legge di una legge
di distribuzione," Giornale delle' Instituto Italiano delgi attuari,
Vol. 4, 1933, pp. 83-91.
8.
Z. W. Birnbaum, "Numerical Tabulation of the Distribution of Kolmogorov's
Statistic for Finite Sample Size," Annals of Mathematical Statistics,
Vol. 47, pp. 425-441.
9.
P. J. Witzke, "Analysis of Confidence Intervals for Probability of
Mission Completion, P(t) = p G(t)," The Johns Hopkins University Applied
Physics Laboratory memorandum F4A-79-275, 19 July 1979.
Reading, Mass.:
Addison-
10.
G. E. Mitzel, "Qualitative Analysis of OTH/DC&T System Concepts (U),"
(Confidential) The Johns Hopkins University Applied Physics Laboratory
memorandum F4A-79-283, 30 July 1979.
11.
The Johns Hopkins University Applied Physics Laboratory, "OTH/DC&T
Engineering Analysis - System Concept Development (U)", (Confidential)
report FS-79-057, December 1979.
12.
Frank A. Tillman, Ching-Lai Bwang, Way Kue, "Optimization Techniques
for System Reliability with Redundancy - A Review," IEEE Transactions
on Reliability, Vol. R-26, No. 3, August, 1977, pp. 148-155.
226
A
SYSTEMS APPROACH
TO COMMAND,
AND COMMUNICATIONS
CONTROL
SYSTEM DESIGN
BY
Jay K. Beam
George D. HaZushynsky
The Johns Hopkins University
Applied Physics Laboratory
Johns Hopkins Road
Laurel, Maryland
20810
This work was supported by the NavaZ EZectronic Systems Command
under Task C2AO of Contract N00024-81-C-5301 with the Department
of the Navy.
227
A SYSTEMS APPROACH TO COMMAND, CONTROL
AND COMMUNICATIONS SYSTEM DESIGN
ABSTRACT
This paper presents the results of recent efforts
by The Johns Hopkins University Applied Physics Laboratory
(JHU/APL) to define a future Command, Control and Communications
(C3 ) system concept that can be used as a basis for developing a
long-range C3 system plan. C3 system structures that could serve
as a basis for future system design are identified.
Research for the technical approach described included:
a) reviewing available Office of the Chief of Naval Operations
(OPNAV) requirements, and b) conducting a series of wargames set
in the 1985-2000 time frame to further define future system requirements and to establish a C3 concept. Based on these wargames, a
C2 functional process has been developed that can be performed
at each Navy command level. This functional process is defined
and expanded to include representative levels of the Navy command
structure, showing the relationship between command levels and
the activities that require functional interaction.
Functions that define the C2 process are grouped into
functional areas. The relationship of these functional areas
is defined in terms of information flow and command and coordination connectivity. Top-level functions and some lower-level
functions associated with each area are identified, discussed,
and defined to more fully convey the generic, functional relationship of the C2 groups.
After the C2 process is defined at a specific command
level, characteristics of a C3 system are identified. Alternative
C2 structures are then defined that would satisfy system characteristics, using the functional model as a building block.
223
I.
INTRODUCTION
A development of Navy Command and Control Systems has
been underway for many years. Most efforts have been directed toward
either a specific command level capability [such as the Tactical Flag
Command Center (TFCC) for an at-sea Battle Group Commander] or fulfilling the need for a commander whose principal role addresses a functional aspect of naval warfare, such as the Anti-Submarine Warfare
Centers Command and Control System (ASWCCCS).
One outgrowth of these efforts has been the proliferation of systems or capabilities directed toward fulfilling the
needs of specific commanders, but ignoring the overall needs of
a Navy C2 system. Therefore, the C0 Project Office of the Naval
Electronic Systems Command (PME-108) requested JHU/APL to undertake a multiyear program to define a circa-2000 C2 system concept
for tactical warfare. The ultimate objective was to provide the
Navy with sufficient information to establish a plan that: a)
could build upon existent Navy C2 capabilities in an evolutionary
manner, and b) allow them to achieve a fully capable system that
would satisfy future naval needs.
Figure 1 shows the general approach taken by JHU/APL
to complete the task. A baseline C 3 system was defined that identified a planned Navy C3 capability, programmed to be available by
1980. This baseline system was examined in a series of wargames
conducted at JHU/APL, which included consideration of the projected
threat to the baseline C 3 system. Out of this wargame experience
comes a C 3 system concept and requirements from which one is able
to identify the functions that a C3 system must perform. Once a
concept has been developed, the functions that a C 3 system must
perform can be determined and, by coupling these functions with
system requirements, it is possible to define a set of systems
that perform the functions and satisfy system requirements. From
this set, a particular system configuration can be selected and
described. The C3 engineering development is still in progress,
and a future C3 system has been described in a Type A System
Specification format, shown in Figure 1.
My objective, here, is to: a) concentrate on the
development of a C3 process or concept, b) translate that process
into a functional representation of the C 3 system, and c) present
some of the considerations involved in defining a C3 system.
229
PROJECTED
C3 THREAT
BASELINE
3
C
SYSTEM
----
3
3
C WARGAMES
C CONCEPT
& ANALYSIS
C3 SYSTEM
REQUIREMENTS
C3 SYSTEM
DEFINITION
.
3
C
FUNCTIONAL
DESCRIPTION'
1
C3 SYSTEM
DESCRIPTION
'TRANSITION
PLAN
Figure 1
TECHNOLOGY
PROJECTIONS
C3 System Engineering Development Project
General Approach
II.
THE C3 PROCESS
Early wargame efforts at JHU/APL revealed that is was
difficult, if not impossible, to examine various aspects of C2
in an analytical manner. Consequently, there was a need to define
C2 as a process or model to be able to treat the various aspects
of C2 in a systematic manner. The process, shown in Figure 2,
resulted from this need, and was a combined effort of several
Laboratory members.
230
V
ENVIRONMENT
E NVIRN
| COMMAND SUPPORT FUNCTIONS
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Figure 2
A Model of the C2 Process
At any command level, friendly, neutral, and hostile
events that occur in an environment are perceived by sensors such
as satellites, radio receivers, radars, sonars, and eyesight.
These events are conveyed horizontally to manual- and computerprocessing subsystems where they are internally labeled and, if
possible, correlated with other events. These functions could,
in theory, be performed nearly automatically by the application
of computer and micro-processor technology. The man-machine interface clearly occurs at the evaluate function. These four functions (sense, process, classify, and evaluate) categorize the command support functions. The model indicates that sensor data are
converted to information as they flow laterally through the C2
process.
The model illustrates the overlap between the command
support and the command functions in recognition of the fact that
the commander's staff, as well as designated evaluators, evaluate
information sets and recommend courses of action.
Command support functions involve the collection,
correlation, evaluation, interpretation and organization of data
and information to produce a reduced information set for command
decisions. Command functions, in contrast, comprise the decisionmaking and force management that direct the actions of subordinates.
Planning or doctrine acts as a filter to reduce the
decision-making burden on the commander. Anticipated events can be
planned for, and appropriate responses can be promulgated by Operation Order (OPORDERs), contingency plans, and rules of engagements.
Events that cannot be covered by prebattle planning require the
commander's attention. He must select a course of action and, after
deciding what response is appropriate, he has three options for
implementing his decision: a) he may choose to delegate authority
in response to a subordinate commander's request, provided the
231
task can be clearly defined. (Given that the subordinate commander
has operational control of necessary resources, he is perceived
by his senior commander to be qualified for the task, and the
senior commander has the means to monitor the actions of the subordinate); b) the senior commander may decide to direct a subordinate commander to carry out a specified course of action; or
c) the senior commander may decide to exercise direct control of
an act performed by a subordinate commander, as in crisis management.
However the selected course of action is implemented,
it impacts the environment, generating events and responses to
the events, which are then sensed, processed, etc. Clearly, C2
is shown to be a closed-loop process.
When we expand the C2 model vertically to encompass
representative echelons of command, as shown in Figure 3, communications are required and the model is expanded to encompass the
C3 process. The overlapping environments for the three command
levels are shown on the left, indicating the differing focus of
each command level. The solid lines indicate the domains of
knowledge, while the dashed-lines indicate that the domain of
interest of the higher command levels encompasses those of the
lower command levels. The mismatch between the solid and dashedlines is intended to reflect present experience where, for a
number of reasons (such as radio silence to avoid alerting the
enemy), a subordinate commander may know more about certain events
than his senior.
The model shows a future need to exchange data at the
processor level in addition to the traditional links for information exchange among evaluators. The evaluator not only correlates
and interprets information processed horizontally, but also may
correlate information received from other levels provided the
communications link is feasible and the value of communicating
outweighs possible penalties.
Also, the model shows the connectivity with higher
command levels [such as National Command Authority (NCA)] as the
establishment of doctrine promulgated in OPORDERs, etc. These
instructions become a part of the planning function, and those
events processed horizontally which can, by doctrine, be delegated
to a lower command level are sent to the evaluate function to be
correlated and ranked with information derived horizontally at
that command echelon.
Out of the act and monitor box, actions that can be
delegated modify the doctrinal filter function at a subordinate
command level. Actions that a senior commander directs a subordinate commander to take either limit or expand the courses of
action available to the subordinate commander. Actions that a
senior commander opts to control directly affect the actions performed at the selected subordinate command level.
232
The process shown in Figure 3 was examined in a series
of wargames conducted at JHU/APL to expose it to an operational
environment and to test the logic of the C2 operations under various warfare roles the U.S. Navy would be expected to encounter.
2
As a result of this examination, the functions that a C system
would be expected to perform were identified and grouped into six
Command, Communication Management, Sensor Manfunctional areas:
2
agement, Engagement Management, Information Management, and C
System Management. Additionally, these functional area groupings
provide a basis for development of functional relationships within
and between command levels and provide a means for the representation of a generic C2 system architecture.
This starting point for development of a system is
defined by the functions (and their structure) present at each
Navy command level examined: Fleet Commander-in-Chief (FLTCINC),
Numbered Fleet, Battle Force/Battle Group, Unit, and Platform.
These functional areas and the connectivities between areas define
the structure present at each command level of the C3 system.
This structure is illustrated in Figure 4, which shows the six
functional areas and the functional connectivities between these
areas at each command level.
DOCTRINE
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The C3 Process
233
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Figure 4
Basic C3 Structure
There are two functional connectivities illustrated
in Figure 4: Information Connectivity and Command and Coordination Connectivity. Information Connectivity is a two-way information flow connecting each functional area with Information
Management. This connectivity provides for the transfer of data
and information to support the functional areas, allows an information base to be maintained and its contents disseminated. The
command portion of the Command and Coordination Connectivity
allows the commander to exercise his authority within the command
level and direct the functional areas. Also, it allows the functional areas to respond to this direction. The coordination portion allows the Engagement, Sensor, Communications, and C2 System
Management functional areas to coordinate their activities within
the constraints established by the commander so that direct command
intervention will not be required.
234
Figure 4 represents a generic building block of the C3
system design alternatives. It is a representation of the functions, structure, and connectivities present at each command level.
With these determined, candidate design alternatives for the C3
system may be described in terms of the connectivities between
functional areas at different command levels and the interfaces
with external commands and information sources.
III.
SYSTEM DESIGN ALTERNATIVES
Integration of our generic building block into the Navy
command structure is shown in Figure 5. It now becomes clear that
the design alternatives for a C3 system can be defined by the manner in which the: various functional areas at each command level
are interconnected, information sources and information management is interfaced, and external interfaces (JOINT/Allied Command
and Combat Systems) are connected to the C3 systems. A tabulation
of these various features and the options associated with each
feature is shown in Table 1. Each design feature has one or more
possible options that may be examined in constructing design alternatives. These options were identified by considering extremes of
the features and a reasonable set between these extremes. The
selection of specific options was influenced by JHU/APL wargame
experience, analytical judgement, and the type of naval operations
the system must support. These options are subject to a number of
constraints that should reduce the possible options. These constraints, and their rationale, are identified in the following
paragraphs.
a. The connectivity between command functional areas
and with the NCA and Joint Commands must provide for an adaptive
hybrid system as defined by the C3 Concept Description.
b. Command functional area connectivities to other
command levels are restricted to command functional areas only.
This is necessary to avoid ambiguous control of forces and assets.
c. The Allied Command interface occurs no lower than
the Battle Force/Battle Group (BF/BG) level. Naval operational
protocol requires liaison to occur with the Officer-in-Tactical
Command (OTC); however, liaison may subsequently be delegated.
d. Information sources shall always interface with
the Information Management areas at their command level. This
represents normal naval operations where elements under the operational control of a particular commander provide information to
that command level.
235
INFORMATION
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236
SYSTEMS
Table 1
Design Features and Options
Features
Options
Command Connectivity
Adaptive Hybrid
NCA/Joint/Allied Command
Interface
NCA/Joint: Adaptive Hybrid
Allied: To BF/BG and Higher Levels
Information Source to Information
Management Area Interface
Centralized: Numbered Fleet
Centralized: BF/BG
Same Level Dissemination
Limited Downward Dissemination
Parallel Downward Dissemination
Full Dissemination
Information Management Area
Connectivity
Centralized: Numbered Fleet
Centralized: BF/BG
Hierarchical
Parallel
Combined Parallel-Hierarchical
Indirect
Asset Management Functional
Area Connectivity
Hierarchical
Parallel
Mixed
Indirect
Combat System Interface
Platform Level
BF/BG and Lower Levels
Single Level Other Than
Platform
e. The connectivities for the functional areas of
Sensor, Communications, Engagement, and C2 System Management to
other command levels are only to functional areas of the same
type (e.g., Sensor to Sensor or Engagement to Engagement) to maintain the integrity of the functional areas as demonstrated by wargame simulation and to prevent disruption of internal command-level
protocols.
237
The design alternative shown in Figure 6 is appropriate for C2 of forces that are essentially self-contained;
e.g.., combat systems require only information that is available
from information sources (sensors) that are actually resident on
the platform, and the exchange of information is only required
between adjacent levels of command. On the other hand, Figure 7
is representative of the case where there is a need for information derived at any command level to be available to the combat
system on a particular platform and, indeed, it is even possible
that the control of a combat system may be vested in a command
that is not resident on the platform. These system capability
"extremes represent only two of the some 80 systems designs
considered in the JHU/APL work for the Navy.
In summary, a systematic approach has proven useful
in identifying the various options available for defining a C2
system for the Navy. JHU/APL has selected and recommended a
system design that will support the application of Naval power
in future years. The design allows development of the required
capability in an evolutionary manner either through the consideration of the needs of individual command levels (such as a platform or a fleet) within the defined C3 system structure or through
development of elements of the system on a functional basis (such
as information management or combat system control). Either
approach leads ultimately to the desired C3 capability and provides a means by which the impact of future combat and sensor
systems can incorporate C3 requirements.
The authors wish to particularly acknowledge Ms. Carol
Fox and Mr. Gerald Preziotti of JHU/APL whose efforts over the
past several years have made this paper possible.
238
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BIBLIOGRAPHY
1.
The Johns Hopkins University Applied Physics Laboratory Confidential
Report
dated March 1978, "Command, Control, and Communication (C ) Requirements and System Concept CIRCA 2000" (U).
2.
The Johns Hopkins University Applied Physics Laboratory Secret Report
FS-78-179, dated July 1978, "C3 Concept Analysis: Phase I Gaining
Results" (U).
3.
The Johns Hopkins University Applied Physics Laboratory Unclassified
Report FS-78-276, dated November 1978, "Future C3 Concepts."
4.
The Johns Hopkins University Applied Physics Laboratory Unclassified
Report FS-79-022, dated January 1979, "YEAR 2000 C3 Concept Briefing"
(U).
5.
The Johns Hopkins University Applied Physics Laboratory Confidential
Report FS-79-016, dated December 1979, "C3 Concept Analysis: Phase
II Gaining Results" (U).
6.
The Johns Hopkins University Applied Physics Laboratory Confidential
Report FS-80-075, dated April 1980, "C 3 System Engineering Development, Phase III War Game Report" (U).
7.
The Johns Hopkins University Applied Physics Laboratory Confidential
Report FS-80-078, dated August 1980, "C3 System Engineering Development - Functional Description" (U).
8.
The Johns Hopkins University Applied Physics Laboratory Secret Report
FS-80-255, dated October 1980, "C3 System Engineering Development Future System Definition" (U).
5S-78-088,
241
242
MEASURES
OF
EFFECTIVENESS
FOR YEAR
2000 TACTICAL
AND PERFORMANCE
C3
SYSTEMS
BY
Djimitri Wiggert
The Johns Hopkins University
Applied Physics Laboratory
Johns Hopkins Road
Laurel, MaryZand
20810
This work was supported by the Naval Electronic Systems Command under
Task C2AO of Contract N00024-81-C-5301 with the Department of the Navy.
243
ABSTRACT
After pointing out the wide variety of terminology now in use,
this paper offers definitions for three classes of system measures:
Measures of Effectiveness (MOEs), Measures of Performance (MOPs), and
Measures of Merit (MOMs). Issues which influence the types of MOEs,
MOPs, and MOMs chosen for an application are discussed, and a rational
method is presented for choosing specific measures for any given
application. Finally, the use of the method is illustrated by describing
its application to the problem of choosing a system design for a Navy
tactical C3 system for the year 2000 and then describing this system at
a Type-A Specification level,
244
MEASURES OF EFFECTIVENESS AND PERFORMANCE
FOR YEAR 2000 TACTICAL C3 SYSTEMS
1. Introduction
The quantitative assessment of a C3 system at any stage of
its development is still very much an art, rather than a science.
This situation is the result of several factors. First, there is no
uniform terminology currently in use. Concepts such as measure of
effectiveness, measure of performance, measure of military worth, measure
of merit, and others have different meanings and different interrelationships
in the hands of different authors. Second, there is frequently a lack of
a usable quantitative definition of a measure, making evaluation difficult.
This problem is subsumed under another, namely, there does not seem to
be any widely used, rational procedure for selecting measures which are
suitable to the particular assessment task, are internally consistent as
a set, and can be evaluated with reasonable ease.
This paper addresses each of these issues. A plea is made for
adoption of uniform terminology as a necessary prerequisite for the
emergence of C3 system assessment as an engineering discipline and for
meaningful and easy exchange of information among workers in this
discipline. A set of attributes is presented which can be applied in
selecting a set of measures for a given situation. Finally, application
of these attributes is described for two stages in the development of
a tactical C3 system for the U.S. Navy in the year 2000 time frame.
2, Terminology
A great variation in terminology is apparent from the literature.
The most widely used term seems to be "measures of effectiveness".
This term, unfortunately, means different things to different people.
It is often used as a "blanket" term to include a spectrum of levels
ranging from various aspects of mission effectiveness (e.g., kill ratio)
to system and subsystem performance (bit error rate, target acquisition
probability, availability) to aspects of procurement and logistics (technical
risk, transportability, interoperability). Such a range of levels occurs,
for example, in References 1-3. In Reference 4, Wohl, Gootkind, and D'Angelo
use the term "measure of merit" in a similar, all-encompassing manner,
These authors do, however, take pains to distinguish between system
,effectiveness from the commander's point of view and system performance
from an engineering point of view. This same distinction is made by
Welch [Reference 6], Van Trees [Reference 7], and Alberts [Reference 8],
among others.
245
In this paper, the distinctions made in References 4, 6, 7, and
8 are applied. The terminology is probably closest in spirit to that of
Welch [Reference 6]. The classes of measures to be used here will be
measures of effectiveness (MOEs), measures of performance (MOPs), and.
measures of merit (MOMs). MOEs will be restricted to those measures
which relate to mission effectiveness, i.e., the commander's viewpoint.
Examples are: probability of mission success, ratio of Red losses to
Blue losses, probability of survival of a specified level of platform
capability, and system flexibility. MOPs will refer to quantities which
are generally of greatest interest to the engineer. Examples include the
aforementioned bit error rate and target acquisition probability,
along with reliability, maintainability, availability, mean time between
failures (MTBF), mean time to repair (MTTR), communication system or
processor throughput rate, and accuracy and timeliness of sensor data.
The third category of measures, MOMs will be used here to encompass
those system attributes which are neither MOEs nor MOPs but which are
nonetheless of equal interest from the overall standpoint of system
acquisition and use. MOMs could include all aspects of cost (development,
production, spares, etc.), technological risk, interoperability,
compatibility, power consumption, and projected obsolescence. Note
that this usage of the term MOM is a departure from the usage in Reference
4, The terminology adopted here has proven useful in the evaluations to be
described in Section 4.
In many applications of MOEs/MOPs/MOMs, it is necessary to
make a choice between qualitative and quantitative measures, and between
relative and absolute measures. The first choice is a function of the
amount of quantitative information available about the system in question,
while the second choice will depend largely on the ability to evaluate
the measures on an absolute scale and possibly on the existence of
absolute standards of effectiveness or performance.
It is clear that there are gray areas between MOEs and MOMs,
i,e,, there are measures which could be viewed as belonging to either
class. This fact, and the terminology adopted in this paper, serve to
underline the need for a uniform terminology.
3, A Method of Selecting a Set of Measures
Another fact which emerges from consideration of the examples
of MOEs and MOPs given in Section 2 is the existence of hierarchies,
both within and between these two types of measures. For example,
mission effectiveness could be considered a top-level MOE, supported by
MOEs flexibility, survivability, and commonality of tactical picture.
These MOEs, in turn, depend on MOPs such as throughput rate, bit error
rate, AJ margin, and physical hardness. Thus, it should be possible to
evaluate measures at any level in a bottom-up manner.
246
------
~-1-~_____
It is perfectly acceptable that measures at one level support
more than one measure at a higher level or are supported by more than one
measure at a lower level. This situation is illustrated in Figure 1.
What is undesirable is that MOEs at any given level be closely coupled or,
worse yet, that an MOE (or MOP) at one level partially supports another
MOE (or MOP) at the same level.
A basic criterion for acceptability of a measure (MOE, MOP, or
MOM) in a given evaluation situation is that the measure be relevant to
the evaluation being performed, For example, in the system design
alternative selection process described in Section 4, the use of bit
error rate would have been totally inappropriate, as would cost,
Mutual independence and relevance are just two of seven attributes
which were found to be extremely useful in selecting an appropriate set of
measures. The complete set, along with definitions of the attributes, is
shown in Table 1. An important advantage of these attributes is that
they can be applied in sequence, so that the set as a whole acts as a
series of "filters" on an original set of candidate MOEs/MOPs/MOMs.
Attributes 1 through 5 are considered essential for any set of measures,
while attributes 6 and 7 are desirable but not vital, and, in fact,
might not necessarily apply to the process of selecting measures in
some situations. The definitions will become more meaningful once the
applications in Section 4 have been discussed.
4. Applications of MOE/MOP/MOM Selection Process
The first application involved the selection of a single Navy
tactical C3 system design alternative from among twelve possible
alternatives, The alternatives and the process leading to their formulation
are described in detail in Reference 9 and summarized in Reference 10.
The problem was to determine the optimum set of connectivities
for the flow of command, coordination, and information among an agreedupon set of basic tactical C 3 functional areas at each of five command
echelons, and between these functional areas and several external functions
and systems (NCA, Allied commands, information sources, and combat systems).
The conceptual relationship among these entities is shown in Figure 2,
This situation differed from most MOE/MOP applications in that implementation
could not even be guessed at. For example, it was beyond the scope of
the problem to consider information exchange or processing rates, or
even propagation media. Thus, any measures chosen had to be independent
of any particular system implementation and set of physical measurement
techniques, in addition to possessing the seven attributes listed in
Table 1. It is clear that the measures should be qualitative rather than
quantitative, and relative rather than absolute. The filtering process
described in Section 3 was applied to a list of nearly forty MOEs/MOPs/MOMs
which had been compiled from a variety of sources, including Reference 1.
There were still nearly twenty survivors at this point, so further analysis
247
LEVEL 1
LEVEL 2
MOE (1,1)
MOE (2,1)
FIGURE 1
HIERARCHY OF MOEs
248
MOE (1,2)
MOE (1,3)
MOE (2,2)
TABLE 1
ATTRIBUTES OF AN IDEAL SET OF MEASURES
Number
Name
Definition
Importance as a measure
General value as a criterion in
selecting or evaluating system
concept, architecture, or implementation;
i.e., what one would like to be able
to use as a measure if at all possible.
2
Applicability to present
situation
Relevance to the selection or
evaluation actually being made.
3
Independence of other
measures
Lack of dependence on or coupling
with other measures to be applied
at same time at the given level.
4
Ease of quantification
Degree to which the measure can be
defined and specified in quantitative
terms.
5
Ease of evaluation
Ease with which values of the
measure can actually be determined
for this application (e.g., by
consensus, judgment, simulation,
field measurement).
6
Independence of scenario
Freedom from the impact of the
choice of a scenario on the outcome
of the application of the measure.
7
Independence of technology
Freedom from the impact which
technology might have on the outcome
of the application of the measure.
249
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was necessary. The final result was a rather broadly defined set of four
MOEs (or system selection criteria, in the context of the problem). These
measures, their working definitions, and relative weights are given in
Table 2, At this point, standard procedures were employed to evaluate
the various connectivity options: a weight was assigned to each of the MOEs
and a qualitative, three-level (-, 0, +) rating scheme was applied to
rate each option relative to each of the others.
As an example of the way in which the options were evaluated
with the use of the MOEs, consider the MOE, Performance, applied to the
connectivity of the Information Management functional areas of Figure 2.
Parallel connectivity of Information Management areas allows all Information
Management areas to share the same integrated tactical picture without
loss of timeliness or accuracy. For this reason, the parallel option was
scored with a plus. The hierarchical connectivity may result in the
greatest loss of timeliness and accuracy because as many as three
intervening nodes may operate on the information, The two centralized
connectivities, in which the numbered fleet (NF) ashore or battle force/
battle group (BF/BG) afloat collects, processes, and then distributes processed
information to all echelons, are only slightly more effective than hierarchical
connectivity, but were scored as possessing medial capability. The results
just stated were entered in the appropriate boxes (shown with heavy border)
in Table 3.
Overall results are summarized numerically in Table 3 and
pictorially in Figure 3, which show that the best options for the four design
features were determined to be the following:
* Parallel downward distribution of the information source
to Information Management area interface.
e Parallel connectivity between the Information Management areas.
* Hierarchical connectivity between the asset management
functional areas,
e Combat system interface at the Platform, Unit, and Battle
Group command levels,
In the second application of the MOE/MOP/MOM selection process,
,the system design alternative selected with the use of the MOEs
described in the preceding paragraphs has been carried into the system
description stage (Reference 11) by means of a modified Type A specification,
which describes in a high-level manner the system effectiveness models
and system performance measures (i.e., MOEs/MOPs/MOMs) which should be
provided and applied by an implementing contractor and by the Navy.
There will be two time-phased stages, each with its own MOE/MOP/MOM
requirements:
251
TABLE 2
TACTICAL C3 SYSTEM DESIGN SELECTION CRITERIA
Definition
Criterion
Weight
Performance
The capability of an option associated with a
particular feature to provide timely, accurate,
and adequate information to, or effective
coordination with, appropriate elements of
the system.
3
Survivability
The capability of an option to perform its
indicated functions (with minimal degradation)
when the loss of one or more nodes or links
occurs.
3
Flexibility
The capability of an option to operate in the
mode of other options associated with that
feature, if so required.
2
Support
The capability of an option associated with a
feature to operate with minimal demands on
communications and/or processing support.
1
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(1) System design, during which models of various implementations of the system will be subjected to tradeoff studies and evaluation.
(2) System implementation [including technical evaluation
(TECHEVAL), operational evaluation (OPEVAL), and fielded systems],
during which exercises and evaluations of designated portions of the
actual C system will be conducted.
At this stage, only proposed measures exist, with the stated
option for the contractor to add or delete measures and/or redefine
one or more measures. Table 4 lists measures which can be applied at
the system design stage, with tentative quantitative definitions. Note
that the MOPs covertness, spoof resistance, and AJ capability are
stated as supporting the higher-level MOPs flexibility, survivability,
and timeliness. Note also that the latter might be argued to be MOEs
rather than MOPs. Finally, observe that the last two items in Table 4
illustrate the concept of MOM as defined in this paper.
Table 5 lists five MOPs which could be applied by a system
evaluator (e.g,, engineer, commander) during prototype system tests,
system evaluations, or field exercises. Because of the desire to
maximize flexibility of approach at this stage, the MOPs in Table 5
violate in some instances the attribute requirements stated in Table 1.
5, Summary and Conclusions
This paper has pointed out the diversity of terminology
presently in use for evaluating C3 systems at various stages in their
evolution. It is hoped that the MOE community will move toward the
adoption of a uniform set of definitions for the various classes and
levels of system measures which must be used. For the C3 system design
evaluation discussed in this paper, three types of measures were defined:
measures of effectiveness (MOEs), performance (MOPs), and merit (MOMs).
MOEs were defined to address operational or mission level effectiveness;
MOPs refer to engineering and logistics-related performance parameters;
and MOMs are all other measures (e.g., cost, risk, interoperability, etc.).
Measures were further categorized as to being quantitative or qualitative,
and relative or absolute, The possible hierarchical nature of a set of
MOEs and MOPs was discussed, particularly the use of lower-level measures
to evaluate higher-level ones. A key result is the development of a
set of seven attributes which can be applied sequentially to a candidate
set of MOEs/MOPs to produce a useful and usable set.
Two applications of this MOE selection process were presented.
These applications involved two successive stages in the development of
a Year 2000 Navy tactical C3 system. These applications clearly illustrate
the impact on choice and evaluation of MOEs of the degree of detail of the
available implementation data. In the first stage, a system design
255
TABLE 4
SYSTEM DESIGN CAPABILITY MEASURES
Capability
Measure
I
Definition
Mission Effectiveness
MOE
Degree to which mission objectives are
accomplished in the required time frame,
measured in terms of friendly-toenemy loss ratio, time to respond to
threat, etc.
Flexibility
MOP
Ease of reconfiguring to another connectivity, capability level, and/or
command structure when commanded to
do so. (Includes number of usable alternate structures and speed of
reconfiguring.)
Survivability
MOP
Probability that system will perform
at a specified level when subjected
to a specified threat (including
partial destruction).
Timeliness
MOP
Time delay within the C3 System in
transferring and processing data,
commands, and coordination information.
Covertness
MOP
Fraction of communication that cannot
be intercepted outside a specified
envelope (supports survivability MOP).
Spoof Resistance
MOP
Fraction of spoofing data rejected
(supports survivability MOP).
Anti-Jamming (AJ)
Capability
MOP
Fraction of links disrupted as function of jammer-to-signal ratio (J/S)
and jamming strategy (supports flexibility, survivability, and timeliness
MOPs).
Ease of Implementation
MOM
Portion of the C System already in
place or which can be implemented with
off-the-shelf or easily developed
hardware or software.
Growth
MOM
Fraction of the C3 System that can be
augmented or improved by simple changes
or additions to its structure at that
time.
256
TABLE 5
SYSTEM PERFORMANCE MEASURES
Definition
Measure
Corrnnality of Tactical Picture
Correlation between targeting data tracks
and between background shipping tracks
held in common by two data bases (afloat
and/or ashore).
Quality of Information Base
Accuracy and timeliness of information
base, including (but not limited to)
coverage radius, maximum time late,
radius of uncertainty, reporting
interval, number of reports per track,
and own and enemy status and plans.
Connectivity
Fraction of node pairs which can communicate at or above some set of performance
levels [e.g., bit error rate (BER),
throughput].
Availability
Fraction of the time a system, subsystem,
or component performs when called upon
at or above some performance level.
Reliability
Fraction of the-time a system, subsystem,
or component satisfactorily performs
throughout a mission when it successfully
began the mission.
Flexibility
Ease of reconfiguring to another connectivity, capability level, and/or command
(Instructure when commanded to do so.
cludes number of usable alternate structures and speed of reconfiguring.)
Covertness
Fraction of communication which cannot
be intercepted outside a specified
envelope.
*Spoof Resistance
Fraction of spoofing data rejected.
AJ Capability
Fraction of links disrupted as function
of J/S and jamming strategy.
257
alternative had to be selected. The total lack of implementation information
forced the choice of broad, qualitative MOEs which were evaluated On a
relative basis. The second stage involved the preliminary recommendation of
MOEs, MOPs, and MOMs to be used by designers, implementers, and commanders
to evaluate simulation results, prototypes, and fielded systems.
258
REFERENCES
1. "Architecture for Tactical Switched Communication Systems - Annex E (II),
Methodology for Design and Analysis", TRI-TAC Office, Fort Monmouth, NJ,
Draft dated 12 May 1981.
2. "Command, Control and Communications (C3 ) Measures of Effecitveness (MOE)
Handbook", Interim Draft, Naval Electronic Systems Command, PME-108,
Washington, D.C., 30 June 1980.
3. "Measures of Effectiveness and Analysis Tools for the Combat System
Architecture Program in the Area of Command Control and Communications",
Progress Report dated June 24, 1979, prepared by Systems Exploration,
Inc., San Diego, CA, for Naval Ocean Systems Center, San Diego, CA,
under Contract No. N00123-76-C-0787.
4. J. G. Wohl, D. Gootkind, and H. D'Angelo, "Measures of Merit for Command
and Control", MTR-8217, The MITRE Corporation, Bedford, MA, 15 June 1981.
5. "Proceedings for Quantitative Assessment of Utility of Command and
Control Systems", MTR-80W00025, The MITRE Corporation, McLean, VA,
January 1980.
6. J. A, Welch, Jr., MG, USAF, "State-of-the-Art of C2 Assessment", in
MTR-80W00025 (Reference 5).
7. H. L. Van Trees, "Keynote Address - Conference Workshop on Quantitative
Assessment of the Utility of Command and Control Systems", in MTR-80W00025
(Reference 5).
8. D. S. Alberts, "C2 I Assessment", in MTR-80W00025 (Reference 5).
9. "Command, Control, and Communications (C3) System Engineering Development
--- Future System Definition", Report FS-80-255 (SECRET), The Johns
Hopkins University Applied Physics Laboratory, Laurel, MD, October, 1980.
10,
J. K. Beam and G. D. Halushynsky, "A Systems Approach to C 3 System Design",
Fourth MIT/ONR Workshop on C3 Systems, San Diego, CA, 26 June 1981.
11.
"Command, Control, and Communications (C3 ) System Engineering Development -YR 2000 System Description (Type A Specification)", Report FS-81-070
(SECRET), The Johns Hopkins University Applied Physics Laboratory, Laurel,
MD, April, 1981.
259
260
AN END
USER FACILITY
CONTROL,
(EUF)
FOR COMMAND,
AND COMMUNICATIONS
(C )
BY
Jan D. WaZd
Sam R. HoZZingsworth
HoneyweZll Systems and Research Center
2600 Ridgway Parkway
Minneapolis, Minnesota 55413
261
AN END USER FACILITY (EUF) FOR COMMAND,
CONTROL, AND COMMUNICATIONS (C3 )
Jan D. Wald and Sam R. Hollingsworth
Honeywell Systems and Research Center
Minneapolis, Minnesota
This paper was prepared for presentation at the fourth annual MIT/ONR workshop
on command, control, and communications (San Diego, 15-26 June 1981). The
purpose of the paper is to outline the following:
C3 problems facing tactical commanders
*
Shortcomings of current C3 systems
o Functional characteristics of an End User Facility for C3 operations
*
Steps required in the development of a C3 EUF
The content of the paper is based in part on experience gained in a variety
of DoD contracts and Honeywell Internal Research and Development (IR&D) projects.
Preparation of the paper was supported by IR&D funds.
The paper reports on an ongoing project at the Systems and Research Center
aimed at developing a C3 system that supports the needs of commanders and
command staffs. We are now in the requirements definition phase of the effort.
The thrust of this work is to utilize tools developed from two branches of
Artificial Intelligence: Cognitive science and knowledge engineering. Cognitive science draws on principles and techniques from computer science,
psychology, linguistics, philosophy, and education. Its emphasis is on explaining
intelligent activities through investigation of human cognitive processes-such as memory, attention, perception, and reasoning--so that they can be put
to use in computer applications. Knowledge engineering focuses upon achieving
expert level performance first by modeling the necessary commander functions
according to principles of cognitive science, and then determining where subject matter expertise is appropriate and supplying it. Using principles of
knowledge engineering, a user supportive EUF can be developed.
We believe tools from these areas of Artificial Intelligence are necessary for
building the kind of EUF which meets the requirements of the C3 environment.
NATURE OF THE PROBLEM
Tactical commanders and their staffs must be prepared to function effectively
under adverse, high-stress conditions. Several factors have a major impact on
the environment of command staffs:
262
e High event rates
*
-
High force densities
-
High movement rates
Increasing complexity of combat systems
-
Proliferation of sensor, weapon, communication, and data
processing systems
-
Expanded capabilities of combat systems
*
Reduced permissible reaction times
*
Interoperability problems
e Disruption and deception by an increasingly capable adversary
*
Personnel problems
-
Increasing skill requirements
-
Decreasing availability of skilled personnel
o Doctrinal turbulence
All indications are that these factors will induce progressively more stress in
the future. In view of these trends, a move toward automating C3 functions is
mandatory and has been undertaken with mixed success in some areas. The Army's
Tactical Fire Direction System (TACFIRE) and Tactical Operations System
(formerly TOS, now SIGMA),and the Air Force's 485L program to automate Tactical
Air Control Center (TACC) are notable examples. Although such systems were
intended to expedite C3 operations, they tended in some respects to have the
opposite effect. The difficulties may be categorized into two major areas:
(1) Hardware/Software problems and (2) User-System interface problems. Examples
of significant hardware/software problems are:
*
*
Information processing capacity limitations
-
Quantity and rate limitations
-
Timelines and accuracy limitations
Information fusion/correlation problems
263
e Data base management problems
- Access by multiple users
-
Retention of current situation and historical trends
- Deletion of obsolete information
e
Information flow problems (related to interoperability problems)
e
Rigid processing algorithms (related to doctrinal turbulence problems)
Recent technological advances are reducing the severity of the hardware/software
problems, but a variety of user-system interface problems continue to plague
automated C3 systems:
e Display complexity
*
Dialog complexity
a
Procedural rigidity
a
Lack of user confidence in the quality of system performance
*
Inappropriate allocation of functions to user and system
-
Presentation of data vs. information
- Excessive user memory requirements
- -Inadequate planning, decision support, and communication functions
9
Need for a trained intermediary (operator) between end user and system
Many of the user-system interface problems have arisen because of a historical
need to hoard memory and processing resources when designing computer systems.
System designers have typically reduced the computer's burden by requiring system
operators to memorize complex codes, abbreviations, and procedures, and by
reducing operator prompts and error messages to a terse minimum. Sophisticated
dialog systems, displays, and input devices have typically been considered
"cosmetic" features that can be dispensed within the competition for budgetary
and hardware/software resources. Experience has shown, however, that system
effectiveness can be seriously compromised when user functions are inadequately
supported.
The need for user-friendly computer systems is becoming increasingly well
recognized, both for commercial and for military applications. Moreover,
technological breakthroughs are simultaneously increasing the capabilities and
264
reducing the cost of hardware/software modules needed for explotating advanced
techniques for user-system interaction.
In light of these developments,
we have begun the process of defining the required functional capabilities of
an automated system to support C3 operations.
APPROACH TO SOLUTION OF THE PROBLEM
Our approach has been to assume that a generic EUF for C3 operations can be
defined and implemented, and that it can significantly improve the force
effectiveness of combat systems. Our long-range objective is to design and
test an EUF for C3 and, ultimately, to tailor the concept to specific C3
domains. Before discussing the steps comprising this plan, the following
paragraphs describe the general concept of an EUF and the general design goals
we are working toward.
Characteristics of an End User Facility
An EUF is an automated workstation designed specifically to support end users.
The support offered by the facility comes from two sources: (1) Its ability
to automate the information management functions necessary to satisfy the
information requirements of users, and (2) its ability to provide an interface
that is natural to use for a wide range of potential users who may differ
from one another in terms of their level of computer sophistication, their
personalities, or their styles of interacting with a computer system.
An EUF uses a user-friendly front end to interact with users. A natural
language interface can potentially be included to facilitate a large class of
user-system transactions. To meet a user's information requirements, an EUF
relies on well defined data bases and supplementary facilities such as
knowledge bases and knowledge based reasoning. Such facilities include the
capability necessary to access, assess, and interpret information from the
domain. They may interpret situational data, for example, or they may support
decision and planning aids for the user.
The ability to handle a variety of users and their individual styles for interacting with a computer system also is built into an EUF. EUFs are designed to
interpret the requests of users and to provide an interface that is both consistent and compatible with their expectations. EUFs also permit user
programmability so that ad hoc information needs can be met.
Scope and Objectives
The EUF we have in mind should be capable of supporting the C3 needs of an Army
division-level commander and staff or equivalent in the Air Force or Navy.
That command level was chosen because it represents a reasonable balance between
the long-range planning functions of higher echelons and the more immediate
265
battle management functions of lower echelons. Our prior experience predisposes
us to think in terms of C3 problems for land combat operations, but we fully
intend to address air and sea operations as well.
Our design goals are as follows:
a
The EUF can be operated directly by the commander and his staff.
Specially trained operators will not be required to serve as
intermediaries between the users and the system.
e The EUF will augment a variety of command functions. It will make
integrated information available to the users, and it will take
coordinated actions in response to command directives.
a
The EUF will impose no training requirements or workload on the users.
e
The users will be able to devote 100% of their attention to tactical
problems, and 0% to the operation of the EUF.
X
The EUF will be designed to promote user acceptance.
The command level we have chosen and the design goals listed above make our
problem challenging, perhaps intractable, but we believe that significant
toward the objectives is currently feasible. The potential payoff
progress
of even partial success appears to be enormous.
Payoffs of an EUF
We have not performed a cost-benefit analysis of an EUF in any C3 domain, but
a well designed EUF would seem to be capable of improving the cost-effectiveness
of combat operations in at least the following ways:
e Improving the ability of the commander and staff to see the battle and
mobilize resources
*
Reducing Che degree of equipment-specific training required for performing C operations
*
Reducing the size requirements for command staffs
e Reducing the skill level requirements for command staffs
These and related payoffs need to be verified, but significant performance
improvements and/or cost reduction in each area appears to be attainable.
266
STEPS TO THE SOLUTION
The remainder of the paper outlines the steps we intend to follow in developing
an EUF for C 3 , provides examples of C3 functions that should be supported by
the EUF, and illustrates what we believe to be the important features and
capabilities of such a facility.
Steps toward Developing an EUF for C3
Our development plan fog the EUF is broken into two major parts. The first is to
develop a generalized C EUF concept and an EUF simulator to test the concept.
The second component is to apply the EUF concept to specific C3 domains.
The first phase is a research and development program designed to develop and
test the basic EUF concept. The steps that are being taken toward developing
the C3 EUF concept are:
e
Analyze C3 functions:
*
Distribute C3 functions between user and EUF:
EUF Simulator
*
Develop user-EUF interface:
a
Test and evaluate the EUF concept
*
Modify and retest the concept
Requirements Definition
Initial design of the
Detailed Design of the EUF Simulator
The product of this program will be a design for a prototype C3 EUF.
Analyze C3 Functions: Requirements Definition--The purpose of the C 3 functional
analysis is to develop a conceptual model of the environment in which the system
is to be placed. The Todel will characterize the information requirements
associated with each C" function. To be effective, these requirements will be
specified in a manner that is independent of the: present way of doing business.
The independence comes from detailing what information is necessary without
describing in the process the present procedures for obtaining or using the
information. The product of the functional analysis is a requirements definition
which describes the functions that must be performed, the data items, and time
factors associated with each C function.
Distribute C3 Functions--The purpose of distributing C3 functions between the
user and the EUF is to begin to develop a top-level design of the EUF. This
step is necessary to ensure that the EUF simulator is a good research and
development tool.
267
Distribution takes place only after a model of command functions is developed.
This modeling begins with the description of the information needs of commanders
as defined during the functional analysis. The knowledge and skills required
for commanders are identified. Based on this model a support plan is devised
and a division of labor is proposed. Some of the activities commanders or their
staffs perform now are assigned to the EUF, others are not. In all cases, the
proposed division of labor should ensure that the eventual users of the EUF will
be free to devote 100% of their time and attention to command functions.
Based on the actual distribution of functions, support facilities and other subsystems will be identified. Those that require subject matter expertise or other
kinds of intelligence will be determined at this time. An initial design of
each will be developed.
Design and Develop EUF Simulator--Based on the distribution of functions and the
initial EUF design, the EUF simulator will be designed and developed. The
user-EUF interface will be developed in detail. A driver scenario will be
simulated with sufficient fidelity to provide realistic test conditions.
The design of the interface must hide the system-related functions from the user.
The intelligent systems to provide this capability will be developed. They must
be able to handle ad hoc queries and alternaitve methods for accessing information. This will guarantee that the EUF will be able to handle individual
differences among users.
Test EUF Concept--The purpose of this step is to test the distribution of
functions and the interface design. A test plan will be developed, followed
by the formulation of a scenario depicting a generic C3 situation. We will
use realistic models of weapon and sensor systems, troop movements, tactics,
and doctrine. Finally, empirical performance data will be collected and
analyzed. In light of the findings of the studies, the EUF concept will be modified as
necessary. The process will be repeated until design changes do not influence
performance.
The second phase of this project is to develop an operational EUF, and to test
it in the field.
Examples of C3 Functions
Table 1 lists a set of major C3 functions and the subfunctions comprising each
one. Each subfunction can be further subdivided into a hierarchicial set of
lower level subfunctions. Although the functions are listed separately in the
table, it is clear that they must be performed in an iterative, tightly interwoven fashion. Most of the functions and subfunctions listed in the table are
currently performed manually by large command staffs. In the Army division-level
context, for example, the G2 staff is responsible for employing the intelligence
268
TABLE 1. EXAMPLES OF C 3 FUNCTIONS
Subfunctions
Major Functions
1.
Know own situation
.
-
*
*
*
*
*
2.
*
Know enemy situation
*
*
*
*
a
3.
*
Plan operations
*
*
o
4.
Conduct operations
e
*
*
*
*
*
269
Establish standing requests for
information
Receive situation reports
Request missing reports
Initiate special requests for
information
Process unsolicited reports
Determine own strengthsi weaknesses,
and capabilities
Establish standing requests for
information
Receive situation reports
Request missing reports
Initiate special requests for
information
Process unsoliciated reports
Determine enemy strengths, weaknesses,
and capabilities
Identify discrepancies between actual and
desired states of the world
Develop plan
Test the plan
Modify the plan if necessary and test again
Generate orders
Distribute orders
Monitor own and enemy situations
Modify plan if necessary, and test
modi fi cati ons
Generate and distribute modified orders
Continue monitoring operations and
update plans as necessary
assets required for seeing the enemy (i,e., knowing the enemy situation). The
G3 staff is tasked with knowing the strengths, capabilities, and current status
of own forces, planning operations, and conducting operations. Similar
functions are performed by Air Force and Navy command staffs. The following
paragraphs summarize the major functions listed in Table 1.
Know Own Situation--In order to develop a picture of the current status of own
forces, the command staff must receive and process situation reports from subordinate units. Most reports will be received on a routine basis according to
standing operating procedures (SOPs) established by the commander. The number
of reports requested by SOPs should be sufficient to produce a data base that
is reasonably detailed and up to date. The number of reports requested should
be held to a reasonable level to, prevent overloading the staff (at either the
sending or receiving end) or communication channels. Emission control considerations may reduce the permissible message traffic to well below the desired
level.
In addition to processing preplanned reports the command staff must perform'
several related functions. The reports should be surveyed to insure that all
expected reports have arrived, and any missing reports should be sought, Special
information not covered by the SOPs may also be required on occasion, In this
case the sources of the information must be identified and the requests for the
information must be formulated and distributed. The command staff should also
be responsive to unsolicited situation reports, particularly emergency reports.
The situation reports must be consolidated into a summary form that characterizes
the current status of friendly units and highlights their strengths, weaknesses,
and capabilities. A graphic representation of unit locations is probably the
most effective way of presenting status information in a form that is useful
for supporting command decisions. Other status information such as supply
level and personnel level for each unit are perhaps more appropriately displayed
in tabular format. The grease pencil is the most common device for conveying
these types of information to the commander although computer driven displays
have been developed for some applications.
Know Enemy Situation--At the subfunction level in Table 1 the steps involved
in characterizing the enemy situation are identical to those discussed above,
At a more detailed level, however, the process is substantially different
because it involves obtaining information about a noncooperative adversary.
The first major problem in attempting to learn the enemy situation is to decide
which intelligence assets to employ. This decision involves detailed knowledge
of the availability and capabilities of the sensor systems and other sources of
intelligence. In addition, emission control considerations and the very real
probability that a sensor system will be destroyed when it is used attach a
potentially high price to the deployment of many of the most valuable active
sensor systems. Passive systems are less vulnerable to this threat, but they
270
also tend to produce data that are more difficult to interpret and evaluate.
The commander must weigh these factors against the expected value of the
information.
Once information requirements have been defined and intelligence resources have
been selected, SOPs and special requests for information can be generated and
distributed.
The information obtained from different sources varies dramatically in terms
of reliability, timeliness, position location accuracy, and type of data
available concerning each enemy unit or movement. These differences combine to
make the task of filtering, correlating, and interpreting multisource data
difficult and time consuming. Some progress has been made in automating the
multisource correlation problem *(e.g., with TACFIRE and as discussed at other
sessions in this conference), but the process remains largely manual in most
command centers.
Plan Operations--The commander's goal in planning an operation is to achieve the
objectives established by higher command, and to expend minimum resources
during the operation. Planning is a complex activity that involves deciding
which forces to mobilize, how to mass them against enemy weaknesses, how to
follow through, and how to provide logistics support to the fighting units.
In addition-, contingency plans need to be developed.
In order to develop a plan the commander must exercise a model of combat
events. The model is often cast in the form of an if-then monologue: "If I
do this, then my adversary will do that and the consequences will be..."
The commander then tests a number of options until one is discovered that yields
a satisfactory expected outcome. That option becomes the plan.
Most such exploratory models are cognitive models. They exist within the
commander and have been developed on the basis of training and experience.
Cognitive models are often extremely powerful, but they are also subject to
severe memory and processing constraints and potentially inappropriate biases.
Some work toward computerizing such gaming models has been accomplished. One
notable example is the Tactical Operations Movement Model under development
by the Army Research Institute, but we are aware of no currently fielded C3
systems that allow commanders to extrapolate into the future from hypothetical
decision points.
Conduct Operations--After a plan has been devised and tested, it must be put
into action. Specific orders must be generated and distributed to the combat
and support untis. The purpose of monitoring own and enemy situations must
continue throughout an operation. Contingency plans may need to be activated
if conditions warrant, or new plans may need to be developed and tested. Any
change in plans must be accompanied by the generation and distribution of new
orders.
271
The generation of orders is typically performed manually at present. Once
generated, the orders are distributed on paper, digitally or by voice over wire
or radio, or in face-to-face meetings. There have been some attempts to
automate these processes, but such automation is currently not common.
Examples of EUF Requirements
Requirements for an EUF for C3 consist of descriptions of the capabilities that
a stand-alone hardware/software system must have. These requirements, because
of our design goals, will be associated both with the functionality necessary
for information as well as user support.
There is some redundancy in the description of the requirements that follow.
This is for purpose of exposition only. The examples chosen for elaboration
are:
*
Situation assessment
*
Decision making and planning
*
Data base management
*
User interface
They represent in a preliminary way the functionality we envision for the EUF.
Only the completed requirements definition, however, can determine the final and
definitive set of requirements.
Situation Assessments
To know own and enemy situations, the EUF must be able to synthesize and correlate information reports, intelligence reports, etc. For this to be done
effectively, a knowledge base and reasoning capability that can exptract
relevant informaion, produce reliable summaries, and make appropriate influences about the state-of-the-world must be available. If the user wants
information that for some reason as yet cannot be obtained, the user should be
able to program the EUF to obtain it.
The EUF must also be able to explain the reasoning behind its assessments. This
requires rules of reasoning and an explanation capability.
Because graphic representations may be more meaningful to commanders than
textual, a text-to-graphics paraphrasing capability may also be necessary.
Providing these summaries and translating from the internal representation
of text to graphics requires a sophisticated translation ability. A natural
language understanding capability may be necessary in order to provide this
functionality.
272
The symbology for the EUF graphic system may look more like an arcade game than
like the graphics of present C3 systems. The design goal is that the user be
placed in non-threatening and familiar circumstances. Using animation, realworld imagery, or other arcade-like facilities may supply this friendly and
supportive _environment.
Decision Making and Planning
To plan and conduct operations adequately, the EUF must support the decision
making and planning functions of the commander and staff. This support should
be able to supply, given a proposed plan, forward looking, realistic projections
of the state-of-the-world. This support should be reality based to the fullest
extent possible.
The support facilities must be knowledge based. They must be able to know the
current state of the operational environment, own and enemy doctrine, and the
capabilities of sensor, weapons, communications, and transportation systems. The
facilities must be able to use this information intelligently to plan and support
the commander and staff.
The recommendations made by the EUF should be based on subject matter expertise.
They should be able to support the user in all phases of decision making and
planning: problem formulation, alternative generation, alternative evaluation,
and alternative selection.
The decision and planning facilities should be able to explain their choice of
selection. The explanation should provide the rationale the system used in
making the selection and, if asked by the user, the system should explain why
other choices were not selected. More detailed explanations should be
available if less detailed ones fail to convince the user. The user should also
be able to modify the criteria used by the EUF, thus allowing the commander to
fine tune the system to meet specific operational and environmental requirements.
Data Base Management
An EUF may have an increadibly large quantity of data/information at its
disposal. A means to organize this data base so that it is useful and timely
is essential. To handle the information requirements of commanders, the EUF must
include an intelligent information retrieval system. The system should include
a high level query language to access the needed information quickly while
minimizing user workload. It must also be able to organize and reorganize its
memory so that it learns about its world and becomes, over time, a better
resource for the user.
The system also must be able to use intelligent heuristics for searching its
memory. Ad hoc information requests can be satisfied this way. Also the utility
of the data base lasts longer and is more flexible. Access paths not specified
during initial data base design can be constructed and the information obtained.
Without intelligent heuristics this would not be possible.
273
User Interface
The user interface should be easy to use, provide a consistent view of the EUF's
functionality, and be compatible with the user's expectations.
There should be a convenient and efficient form of dialog. The dialog should
be natural language oriented. A full-blown natural language understanding
system may not be required. A menu-select or fill-in-the-blank entry format
may be sufficient. However, the interface system should incorporate features
that make the formulation of complex queries and user programmability easy
and natural.
The interface should be multi-modal.
are:
Design features that may be appropriate
o Automatic voice recognition and synthesis
9
An alphanumeric keyboard and display
*
Special function keys
*
Graphics capability
Human factors design guidelines should be followed to minimize workload and
maximize operational effectiveness. The display modes used must be powerful
enough to produce the natural, supportive environment the EUF requires. Real
time information management is essential whether textual or graphic. In a
gaming situation or during situation assessment, time compression is a useful
tool. In some cases, a display such as would appear in a process control
environment may be more useful than text. This is another instance when an
arcade-like environment may be most appropriate.
CONCLUSIONS
In summary, we are in the initial stages of an IR&D program to develop an EUF
to support the needs of commanders and their staffs. The system will employ
techniques from the domains of artificial intelligence and knowledge engineering
to support tactical data acquisition and analysis, planning, and force management functions. Advanced automation and human factors techniques will be used
to transfer as much of the workload from the commander and staff to the system
as possible, thus allowing the users to focus their attention on the developing
tactical situation rather than equipment operation per se. We anticipate that
the successful development and fielding of an EUF for C3 would yield a significant
payoff in terms of increased combat effectiveness of C3 systems.
274
APPENDIX
FOURTH MIT/ONR WORKSHOP ON
DISTRIBUTED INFORMATION AND DECISION SYSTEMS
MOTIVATED BY COMMAND-CONTROL-COMMUNICATIONS
(C ) PROBLEMS
June 15, 1981 through June 26, 1981
San Diego, California
List of Attendees
Table of Contents Volumes I-IV
275
MIT/ONR WORKSHOP OF DISTRIBUTED INFORMATION AND DECISION SYSTEMS
MOTIVATED BY COMMAND-CONTROL-COMMUNICATIONS
JUNE 15, 1981
-
(C3 ) PROBLEMS
JUNE 26, 1981
ATTENDEES
David S. AZberts
Special Asst. to Vice President
& General Manager
The MITRE Corporation
1820 Dolley Madison Blvd.
McLean, VA 22102
Tel: (703) 827-6528
Vidyadhana Raj AviZZa
Electronics Engineer
Naval Ocean Systems Center
Code 8241
San Diego, CA 92152
Tel: (714) 225-6258
Dennis J. Baker
Research Staff
Naval Research Laboratory
Code 7558
Washington DC 20375
Tel: (202) 767-2586
GZen AlZgaier
Electronics Engineer
Naval Ocean Systems Center
Code 8242
San Diego, CA 92152
Tel: (714) 225-7777
Ami Arbel
Senior Research Engineer
Advanced Information & Decision Systems
201 San Antonio Circle #201
Mountain View, CA 94040
Tel: (415) 941-3912
Michael A thans
Professor of Electrical Engineering
& Computer Science
Laboratory for Information and
Decision Systems
Massachusetts Institute of Technology
Room 35-406
Cambridge, MA 02139
Tel: (617) 253-6173
DanielZ A. Atkinson
Executive Analyst
CTEC, Inc.
7777 Leesburg Pike
Falls Church, VA 22043
Tel: (703) 827-2769
Alan R. Barnum
Technical Director
Information Sciences Division
Rome Air Development Center
Griffiss AFB, NY 13441
Tel: (315) 330-2204
Jay K. Beam
Senior Engineer
Johns Hopkins University
Applied Physics Laboratory
Johns Hopkins Road
Laurel, MD 20810
Tel: (301) 953-7100 x3265
Robert Bechtel
Scientist
Naval Ocean Systems Center
Code 8242
San Diego, CA 92152
Tel: (714) 225-7778
276
ATTENDEES C3 CONFERENCE
PAGE TWO
VitaZius Benokraitis
Alfred Brandstein
Mathematician
US ARMY Material Systems Analysis
ATTN: DRXSY - AAG
Aberdeen Proving Ground, MD 21005
Tel:
Systems Analysis Branch
CDSA MCDEC USMC
Quantico, VA 22134
Tel: (703) 640-3236
(301) 278-3476
James V. Bronson
Lieutenant Colonel USMC
Naval Ocean Systems Center
MCLNO Code 033
San Diego, CA 92152
Tel: (714) 225-2383
Patricia A. BiZZllings ey
Research Psychologist
Navy Personnel R&D Center
Code 17
San Diego, CA 92152
Tel: (714) 225-2081
Rudolph C. Brown, Sr.
Westinghouse Electric Corporation
P. 0. 746
MS - 434
Baltimore, MD 21203
Tel:
WiZZiam B. Bohan
Operations Research Analyst
Naval Ocean Systems Center
Code 722
San Diego, CA 92152
Tel: (714) 225-7778
Thomas G. Bugenhagen
Group Supervisor
Applied Physics Laboratory
Johns Hopkins University
Johns Hopkins Road
Laurel, MD 20810
Tel: (301) 953-7100
James Bond
Senior Scientist
Naval Ocean Systems Center
Code 721
San Diego, CA 92152
Tel: (714) 225-2384
James R.
PauZ L.
Bongiovanni
CaZZllan
Research Psychologist
Research Engineer
Naval Underwater Systems Center
Code 3521 Bldg. 1171-2
Newport, RI 02840
Tel: (401) 841-4872
Navy Personnel R&D Center
Code 302
San Diego, CA 92152
Tel: (714) 225-2081
Christopher Bowman
Research Associate
Member, Technical Staff
VERAC, Inc.
10975 Torreyana Road
Suite 300
San Diego, CA 92121
Tel: (714) 457-5550
Laboratory for Information and
Decision Systems
Massachusetts Institute of
Technology
Room 35-331
Caibridge, MA 02139
Tel: (617) 253-2125
David Castanon
277
ATTENDEES C3 CONFERENCE
PAGE THREE
S. I. Chou
Robin DiZZllard
Engineer
Naval Ocean Systems Center
Code 713B
San Diego, CA 92152
Tel: (714) 225-2391
Mathematician
Naval Ocean Systems Center
Code 824
San Diego, CA 92152
Tel: (714) 225-7778
Gerald A. CZapp
EZizabeth R. Ducot
Physicist
Naval Ocean Systems Center
Code 8105
San Diego, CA 92152
Tel: (714) 225-2044
Research Staff
Laboratory for Information and
Decision Systems
Massachusetts Institute of
Technology
Room 35-410
Cambridge, MA 02139
Tel: (617) 253-7277
DougZas Cochran
Scientist
Bolt Beranek & Newman Inc.
50 Moulton Street
Cambridge, MA 02138
Tel: (415) 968-9061
DonaZd R. Edmonds
Group Leader
MITRE Corporation
1820 Dolley Madison Blvd.
McLean, VA 22102
Tel: (702) 827-6808
A. Brinton Cooper, III
Chief, C3 Analysis
US ARMY Material Systems Analysis
ATTN: DRXSY-CC
Aberdeen Proving Ground, MD 21005
Tel: (301) 278-5478
Martin Einhorn
Scientist
Systems Development Corporation
4025 Hancock Street
San Diego, CA 92110
Tel: (714) 225-1980
David E. Corman
Engineer
Jonhs Hopkins University
Applied Physics Laboratory
Johns Hopkins Road
Laurel, MD 20810
Tel: (301) 953-7100 x521
Leon Ekchian
Graduate Student
Laboratory for Information and
Decision Systems
Massachusetts Institute of
Technology
Room 35-409
WiZbur B. Davenport, Jr.
Professor of Communications Sciences
& Engineering
Laboratory for Information and
Decision Systems
Massachusetts Institute of Technology
Room 35-214
Cambridge, MA 02139
Tel: (617) 253-2150
Cambrdige, MA 02139
Tel: (617) 253-5992
Thomas Fortmann
Senior Scientist
Bolt, Beranek & Newman, Inc.
50 Moulton Street
Cambridge, MA 02138
Tel2
278
(617) 497-3521
ATTENDEES C 3 CONFERENCE
PAGE FOUR
Clarence J. Funk
Peter P. Groumpos
Scientist
Naval Ocean Systems Center
Code 7211, Bldg. 146
San Diego, CA 92152
Tel: (714) 225-2386
Professor of Electrical Eng.
Cleveland State University
Cleveland, OH 44115
Tel: (216) 687-2592
George D. Halushynsky
Mario Gerla
Professor of Electrical Engineering
& Computer Science
University of California
Los Angeles
Boelter Hall 3732H
Los Angeles, CA 90024
Tel: (213) 825-4367
Member of Senior Staff
Johns Hopkins University
Applied Physics Laboratory
Johns Hopkins Road
Laurel, MD 20810
Tel: (301) 953-7100 x2714
Scott Harmon
Donald T. GiZes, Jr.
Electronics Engineer
Naval Ocean Systems Center
Code 8321
San Diego, CA 92152
Tel: (714) 225-2083
Technical Group
The MITRE Corproation
1820 Dolley Madison Bldv.
McLean, VA 22102
Tel: (703) 827-6311
David Haut
Irwin R. Goodman
Research Staff
Naval Ocean Systems Center
Code 722
San Diego, CA 92152
Tel: (714) 225-2014
Scientist
Naval Ocean Systems Center
Code 7232
Bayside Bldg. 128 Room 122
San Diego, CA 92152
Tel: (714) 225-2718
C. W. HeZlstrom
Professor of Electrical Eng.
& Computer Science
Frank Greitzer.
University of California,
San Diego
La Jolla, CA 92093
Research Psychologist
Navy Personnel R&D Center
San Diego, CA 92152
Tel:
Tel;
(714) 225-2081
(714) 452-3816
Leonard S. Gross
Ray L. Hershman
Member of Technical Staff
VERAC, Inc.
10975 Torreyana Road
Suite 300
San Diego, CA 92121
Tel: (714) 457-5550
Research Psychologist
Navy Personnel R&D Center
Code P305
San Diego, CA 92152
Tel: (714) 225-2081
279
ATTENDEES C 3 CONFERENCE
PAGE FIVE
Sam R. HoZllingsworth
CarroZll K. Johnson
Senior Research Scientist
Honeywell Systems & Research Center
2600 Ridgway Parkway
Minneapolis, MN 55413
Tel: (612) 378-4125
Visiting Scientist
Naval Research Laboratory
Code 7510
Washington DC 20375
Tel: (202) 767-2110
Kuan-Tsae Huang
Jesse Kasler
Graduate Student
Laboratory for Information and
Decision Systems
Massachusetts Institute of Technology
Room 35-329
Cambridge, MA 02139
Tel: (617) 253-
Electronics Engineer
Naval Ocean Systems Center
Code 9258, Bldg. 33
San Diego, CA 92152
Tel: (714) 225-2752
Richard T. KeZZlley
James R. Hughes
Major, USMC
Concepts, Doctrine, and Studies
Development Center
Marine Corps Development & Education
Quantico, VA 22134
Tel: (703) 640-3235
Research Psychologist
Navy Personnel R&D Center
Code 17 (Command Systems)
San Diego, CA 92152
Tel:
(714) 225-2081
David KZeinman
Professor of Electrical Eng.
& Computer Science
University of Connecticut
Kent S.
HuZZ
Box U-157
Commander, USN
Deputy Director,
Mathematical & Information Sciences
Office of Naval Research
Code 430B
800 N. Quincy
Arlington, VA 22217
Tel: (202) 696-4319
Storrs, CT 06268
Tel: (203) 486-3066
CaroZyn Hutchinson
Robert C. KoZb
Head Tactical Command
& Control Division
Naval Ocean Systems Center
Code 824
San Diego, CA 92152
Tel: (714) 225-2753
Systems Engineer
Comptek Research Inc.
10731 Treena Street
Suite 200
San Diego, CA 92131
Tel: (714) 566-3831
MichaeZ Kovacich
Systems Engineer
Comptek Research Inc.
Mare Island Department
P.O. Box 2194
Vallejo, CA 94592
Tel: (707) 552-3538
280
ATTENDEES C3 CONFERENCE
PAGE SIX
Timothy Kraft
AZexander H. Levis
Systems Engineer
Comptek Research, Inc.
10731 Treena Street
Suite 200
San Diego, CA 92131
Tel: (714) 566-3831
Senior Research Scientist
Laboratory for Information and
Decision Systems
Massachusetts Institute of
Technology
Room 35-410
Cambridge, MA 02139
Tel: (617) 253-7262
Manfred Kraft
Diplom-Informatiker
Victor O.-K. Li
Hochschule der Bundeswehr
Fachbereich Informatik
Werner-Heissenbergweg 39
8014 Neubiberg, West Germany
Tel: (0049) 6004-3351
Professor of Electrical Eng,
& Systems
PHE
University of Southern California
Los Angeles, CA 90007
Tel: (213) 743-5543
Leslie Kramer
Senior Engineer
ALPHATECH, Inc.
3 New England Executive Park
Burlington, MA 01803
Tel: (617) 273-3388
Glenn R. Linsenmayer
Westinghouse Electric Corporation
P. O. Box 746 - M.S. 434
Baltimore, MD 21203
Tel: (301) 765-2243
Ronald W. Larsen'
Pan-Tai Liu
Division Head
Naval Ocean Systems Center
Code 721
San Diego, CA 92152
Tel: (714) 225-2384
Professor of Mathematics
University of Rhode Island
Kingston, RI 02881
Tel: (401) 792-1000
Joel S. Lawson, Jr.
Chief Scientist C31
Naval Electronic Systems Command
Washington DC 20360
Tel: (202) 692-6410
Graduate Student
Laboratory for Information and
Decision Systems
Massachusetts Institute of
Technology
Room 35-403
Cambridge, MA 02139
Tel: 617) 253-2163
Robin Magonet-Neray
Dan Leonard
Electronics Engineer
Naval Ocean Systems Center
Kevin MaZZoy
Code 8105
SCICON Consultancy
San Diego, CA 92152
Tel: (714) 225-7093
Sanderson House
49, Berners Street
London W1P 4AQ, United Kingdom
Tel: (01) 580-5599
281
ATTENDEES C3 CONFERENCE
PAGE SEVEN
Dennis C. McCaZZ
Mathematician
Naval Ocean Systems Center
Code 8242
San Diego, CA 92152
Tel: (714) 225-7778
Charles L. Morefield
Board Chairman
VERAC, Inc.
10975 Torreyana Road
Suite 300
San Diego, CA 92121
Tel: (714) 457-5550
Marvin Medina
Scientist
Naval Ocean Systems Center
San Diego, CA 92152
Tel: (714) 225-2772
Peter Morgan
SCICON Consultancy
49-57, Berners Street
London W1P 4AQ, United Kingdom
Tel: (01) 580-5599
Michael Melich
Head, Command Information
Systems Laboratory
Naval Research Laboratory
Code 7577
Washington DC 20375
Tel: (202) 767-3959
John S. Morrison
Captain, USAF
TAFIG/IICJ
Langeley AFB, VA 23665
Tel: (804) 764-4975
John MeZviZle
Naval Ocean Systems Center
Code 6322
San Diego, CA 92152
Tel: (714) 225-7459
MichaeZ S. Murphy
Member of Technical Staff
VERAC, Inc.
10975 Torreyana Road
Suite 300
San Diego, CA 92121
Tel: (714) 357-5550
Glenn E. MitzeZ
Engineer
Johns Hopkins University
Applied Physics Laboratory
Johns Hopkins Road
Laurel, MD 20810
Tel: (301) 953-7100 x2638
Jim Pack
Naval Ocean Systems Center
Code 6322
San Diego, CA 92152
Tel: (714) 225-7459
Bruce Patyk
Naval Ocean Systems Center
Code 9258, Bldg. 33
San Diego, CA 92152
Tel: (714) 225-2752
Michael H. Moore
Senior Control System Engineer
Systems Development Corporation
4025 Hancock Street
San Diego, CA 92037
Tel: (714) 225-1980
282
ATTENDEES C
PAGE EIGHT
CONFERENCE
RoZand Payne
Barry L. Reichard
Vice President
Advanced Information & Decision Systems
201 San Antonio Circle #286
Mountain View, CA 94040
Tel: (415) 941-3912
Field Artillery Coordinator
US Army Ballistic Research
Laboratory
ATTN: DRDAR-BLB
Aberdeen Proving Ground, MD 21014
Tel: (301) 278-3467
Anastassios Perakis
Graduate Student
Ocean Engineering
Massachusetts Institute of Technology
Room 5-426
Cambridge, MA 02139
Tel: (617) 253-6762
David Rennels
Professor of Computer Science
University of California, LA
3732 Boelter Hall
Los Angeles, CA 90024
(213) 825-2660
Tel:
Lloyd S. Peters
Thomas P. Rona
Associate Director
Center for Defense Analysis
SRI International
EJ352
333 Ravenswood Avenue
Menlo Park, CA 94025
Tel: (415) 859-3650
Staff Scientist
Boeing Aerosapce Company
MS 84-56
P. O. Box 3999
Seattle, WA 98124
Tel: (206) 773-2435
Nils R. Sande ZZ, Jr.
President & Treasurer
HariZaos N. Psaraftis
Professor of Marine Systems
Massachusetts Institute of Technology
Room 5-213
Cambridge, MA 02139
Tel: (617) 253-7639
Paul M.
ALPHATECH, Inc.
3 New England Executive Park
Burlington, MA 01803
Tel: (617) 273-3388
DanieZ Schutzer
Technical Director
Reeves
Electronics Engineer
Naval Ocean Systems Center
Naval Intelligence
Chief of Naval Operations
Code 632
San Diego, CA 92152
Tel: (714) 225-2365
NOP 009T
Washington DC 20350
Tel: (202) 697-3299
283
ATTENDEES C3 CONFERENCE
PAGE NINE
Adrian SegaZZll
T. Tao
Professor of Electrical Engineering
Technion IIT
Haifa, Israel
Tel: (617) 253-2533
Professor
Naval Postgraduate School
Code 62 TV
Monterey, CA 93940
Tel: (408) 646-2393 or 2421
Prodip Sen
H. Gregory Tornatore
Polysystems Analysis Corporation
P. O. Box 846
Huntington, NY 11743
Tel: (516) 427-9888
Johns Hokpins University
Applied Physics Laboratory
Johns Hopkins Road
Laurel, MD 20810
Tel: (301) 953-7100 x2978
HarZan Sexton
Edison Tse
Naval Ocean Systems Center
Code 6322
San Diego, CA 92152
Tel: (714) 225-2502
Professor of Engineering
Economic Systems
Stanford University
Stanford, CA 94305
Tel: (415) 497-2300
Mark J. Shensa
Naval Ocean Systems Center
Code 6322
San Diego, CA 92152
Tel: (714) 225-2349 or 2501
E.
J. R. Simpson
Office of Naval Research
800 N. Quincy
Arlington, VA 22217
Tel:
B.
TurnstaZZll
Head, Ocean Surveillance
Systems Department
Naval Ocean Systems Center
Code 72
San Diego, CA 92152
Tel:
(714) 225-7900
Lena Valavani
Research Scientist
Laboratory for Information and
Decision Systems
Massachusetts Institute of
Technology
Room 35-437
Cambridge, MA 02139
Tel: (617) 253-2157
(202) 696-4321
Stuart H. Starr
Director Systems Evaluation
The Pentagon
DUSD (C31), OSD
Room 3E182
Washington DC 20301
Tel: (202) 695-9229
284
ATTENDEES C
PAGE TEN
CONFERENCE
ManieZ Vineberg
Richard P. Wishner
Electronics Engineer
Naval Ocean Systems Center
Code 9258
San Diego, CA 92152
Tel: 714) 225-2752
President
Advanced Information & Decision
Systems
201 San Anotnio Circle
Suite 286
Mountain View, CA 94040
Tel: (415) 941-3912
Joseph H. Wack
Advisory Staff
Westinghouse Electric Corporation
P. O. Box 746 MS-237
Baltimore, MD 21203
Tel: (301) 765-3098
Joseph G. WohZ
V. P. Research & Development
ALPHATECH, Inc.
3 New England Executive Park
Burlington, MA 01803
Tel:
(617) 273-3388
Jan D. Wald
Senior Research Scientist
Honeywell Inc.
John M. Wosencraft
Systems & Research Center
MN 17-2307
P. O. Box 312
Minneapolis, MN 55440
Tel: (612) 378-5018
Head of C3 Curriculum
Naval Postgraduate School
Code 74
Monterey, CA 93940
Tel: (408) 646-2535
Bruce K. Walker
Lofti A. Zadeh
Professor of Systems Engineering
Case Western Reserve University
Cleveland, OH 44106
Tel: (216) 368-4053
Professor of Computer Science
University of California
Berkeley, CA 94720
Tel: (415) 526-2569
David White
Advanced Technology, Inc.
2120 San Diego Avenue
Suite 105
San Diego, CA 92110
Tel: (714) 981-9883
Jeffrey E. WieseLthier
Naval Research Laboratory
Code 7521
Washington DC 20375
Tel: (202) 767-2586
285
SURVEILLANCE
FOREWORD
AND
TARGET
TRACKING
.....................................................
DATA DEPENDENT ISSUES IN SURVEILLANCE PRODUCT INTEGRATION
Dr. Daniel A. Atkinson ..........................................
MEMORY DETECTION MODELS FOR PHASE-RANDOM OCEAN ACOUSTIC FLUCTUATIONS
Professor Harilaos N. Psaraftis, Mr. Anatassios Perakis, and
Professor Peter N. MikhaheZvsky .................................
DETECTION TRESHOLDS FOR MULTI-TARGET TRACKING IN CLUTTER
Dr. Thomas Fortmann,Professor Yaakov Bar-ShaZom, and
Dr. MoZZy Scheffe ...............................................
MULTISENSOR MULTITARGET TRACKING FOR INTERNETTED FIGHTERS
Dr. Christopher L. Bowman .......................................
MARCY:
A DATA CLUSTERING AND FUSION ALGORITHM FOR MULTI-TARGET
TRACKING IN OCEAN SURVEILLANCE
Dr. Michael H. Moore ............................................
AN APOSTERIORI APPROACH TO THE MULTISENSOR CORRELATION OF DISSIMILAR
SOURCES
Dr. MichaeZ M. Kovacich ........................................
A UNIFIED VIEW OF MULTI-OBJECT TRACKING
Drs. Krishna R. Pattipati, Nils R. SandeZZ, Jr., and
Leslie C. Kramer ................................................
OVERVIEW OF SURVEILLANCE RESEARCH AT M.I.T.
Professor Robert R. Tenney ......................................
A DIFFERENTIAL GAME APPROACH TO DETERMINE PASSIVE TRACKING MANEUVERS
and Professor Pan-T. Liu ...............
Dr. PauZ L. Bongiovanni
286
DESCRIPTION OF AND RESULTS FROM A SURFACE OCEAN SURVEILLANCE
SIMULATION
Drs. Thomas G. Bugenhagen, Bruce Bundsen, and
Lane B. Carpenter .............................................
AN
OTH SURVEILLANCE CONCEPT
Drs. LesZie C. Kramer and Nils R. SandeZZ, Jr .................
APPLICATION OF AI METHODOLOGIES TO THE OCEAN SURVEILLANCE
PROBLEM
Drs. Leonard S. Gross, MichaeZ S. Murphy, and
CharZes L. Morefield ..........................................
A PLATFORM-TRACK ASSOCIATION PRODUCTION
SUBSYSTEM
Ms. Robin DiZZllard .............................................
287
II
SYSTEM ARCHITECTURE AND EVALUATION
FOREWORD
................................................
C I SYSTEMS EVALUATION PROGRAM
Dr. Stuart H. Starr .........................................
C
SYSTEM RESEARCH AND EVALUATION: A SURVEY AND ANALYSIS
Dr. David S. AZberts ........................................
THE INTELLIGENCE ANALYST PROBLEM
Dr. DanieZ Schutzer .........................................
DERIVATION OF AN INFORMATION PROCESSING SYSTEMS (C3/MIS)
-ARCHITECTURAL MODEL -- A MARINE CORPS PERSPECTIVE
Lieutenant CoZoneZ James V. Bronson .........................
A CONCEPTUAL CONTROL MODEL FOR DISCUSSING COMBAT DIRECTION
SYSTEM (C2 ) ARCHITECTURAL ISSUES
Dr. Timothy Kraft and Mr. Thomas Murphy .....................
EVALUATING THE UTILITY OF JINTACCS MESSAGES
Captain John S. Morrison .....................................
FIRE SUPPORT CONTROL AT THE FIGHTING LEVEL
Mr. Barry L. Reichard .......................................
A PRACTICAL APPLICATION OF MAU IN PROGRAM DEVELOPMENT
Major James R. Hughes ........................................
HIERARCHICAL VALUE ASSESSMENT IN A TASK FORCE DECISION ENVIRONMENT
Dr.
Ami ArbeZ ............................................
288
OVER-THE-HORIZON, DETECTION, CLASSIFICATION AND TARGETING
(OTH/DC&T) SYSTEM CONCEPT SELECTION USING FUNCTIONAL FLOW
DIAGRAMS
Dr. GZenn E. MitzeZ .........................................
A SYSTEMS APPROACH TO COMMAND, CONTROL AND COMMUNICATIONS
SYSTEM DESIGN
Dr. Jay K. Beam and Mr. George D. Haluschynsky ..............
MEASURES OF EFFECTIVENESS AND PERFORMANCE FOR YEAR 2000
TACTICAL C3 SYSTEMS
Dr. Djimitri Wiggert ........................................
AN END USER FACILITY
COMMUNICATIONS (C3 )
(EUF) FOR COMMAND, CONTROL, AND
Drs. Jan D. Wald and Sam R. Hollingsworth ...................
289
COMMUNICATION,
FOREWORD
DATA BASES
& DECISION SUPPORT
................................................
RELIABLE BROADCAST ALGORITHMS IN COMMUNICATIONS NETWORK
Professor Adrian SegaZZ .....................................
THE HF INTRA TASK FORCE COMMUNICATION NETWORK DESIGN STUDY
Drs. Dennis Baker, Jeffrey E. Wieseithier, and
Anthony Ephremides .....................................
FAIRNESS IN FLOW CONTROLLED NETWORKS
Professors Mario GerZa and Mark Staskaukas ..................
PERFORMANCE MODELS OF DISTRIBUTED DATABASE
Professor Victor O.-K. Li ...................................
ISSUES IN DATABASE MANAGEMENT SYSTEM COMMUNICATION
Mr. Kuan-Tase Huang and Professor Wilbur B. Davenport, Jr..
MEASUREMENT OF INTER-NODAL DATA BASE COMMONALITY
Dr. David E. Corman .........................................
MULTITERMINAL RELIABILITY ANALYSIS OF DISTRIBUTED PROCESSING
SYSTEMS
Professors Aksenti Grnarov and Mario GerZa ..................
FAULT TOLERANCE IMPLEMENTATION ISSUES USING CONTEMPORARY
TECHNOLOGY
Professor David RenneZs .....................................
APPLICATION OF CURRENT AI TECHNOLOGIES TO C2
Dr. Robert Bechtal ..........................................
290
A PROTOCOL LEARNING SYSTEM FOR CAPTURING DECISION-MAKER LOGIC
Dr. Robert BechtaZ ...........................................
ON USING THE AVAILABLE GENERAL-PURPOSE EXPERT-SYSTEMS PROGRAMS
Dr. Carroll K. Johnson .......................................
291
IV
C
FOREWORD
THEORY
.................................................
RATE OF CHANGE OF UNCERTAINTY AS AN INDICATOR OF COMMAND
AND CONTROL EFFECTIVENESS
Mr. Joseph G. WohZ ...........................................
THE ROLE OF TIME IN A COMMAND CONTROL SYSTEM
Dr. Joel S. Lawson, Jr ......................................
GAMES WITH UNCERTAIN MODELS
Dr. David Castanon ...........................................
INFORMATION PROCESSING IN MAN-MACHINE SYSTEMS
Dr. Prodip Sen and Professor Rudolph F. Drenick ..............
MODELING THE INTERACTING DECISION MAKER WITH BOUND RATIONALITY
Mr. Kevin L. Boettcher and Dr. Alexander H. Levis ............
DECISION AIDING -- AN ANALYTIC AND EXPERIMENTAL STUDY IN A
MULTI-TASK SELECTION PARADIGM
Professor David L. Kleiman and Drs. Eric P. Soulsby, and
Krishna R. Pattipati ...............................
FUZZY PROBABILITIES AND THEIR ROLE IN DECISION ANALYSIS
Professor
Lotfi A. Zadeh ....................................
3
COMMAND, CONTROL AND COMMUNICATIONS (C
) SYSTEMS MODEL
AND MEASURES OF EFFECTIVENESS (MOE's)
Drs. Scot Harmon and Robert Brandenburg ......................
THE EXPERT TEAM OF EXPERTS APPROACH TO C
ORGANIZATIONS
Professor Michael Athans .....................................
292
A CASE STUDY OF DISTRIBUTED DECISION MAKING
Professor Robert R. Tenney ...................................
ANALYSIS OF NAVAL COMMAND STRUCTURES
Drs. John R. DeZaney, NilZs R. SandeZZ, Jr., Leslie C. Kramer,
and Professors Robert R. Tenney and Michael Athans ...........
MODELING OF AIR FORCE COMMAND AND CONTROL SYSTEMS
Dr. Gregory S. Lauer, Professor Robert R. Tenney, and
Dr. Nils R. SandeZZ, Jr .....................................
A FRAMEWORK FOR THE DESIGN OF SURVIVABLE DISTRIBUTED SYSTEM
-- PART I:
COMMUNICATION SYSTEMS
Professors Marc Buchner and Victor Matula: presented
by Professor Kenneth Loparo ..................................
A FRAMEWORK FOR THE DESIGN OF SURVIVABLE DISTRIBUTED SYSTEMS
-- PART II:
CONTROL AND INFORMATION STRUCTURE
Professors Kenneth Loparo, Bruce Walker and Bruce Griffiths ..
CONTROL SYSTEM FUNCTIONALIZATION OF C- SYSTEMS VIA TWO-LEVEL
DYNAMICAL HIERARCHICAL SYSTEMS (DYHIS)
Professor Peter P. Groumpos ..................................
SEQUENTIAL LINEAR OPTIMIZATION & THE REDISTRIBUTION OF ASSETS
Lt. CoZoneZ Anthony Feit and Professor John M. Wozencraft ....
C
AND WAR GAMES -- A NEW APPROACH
Dr. Alfred G. Brandstein .....................................
293