An Integrated Command and Control
Architecture for Unmanned Systems
for 2030
Systems Engineering and Analysis
Cohort-16
Integrated Project Tasking
• Develop a Joint Systems concept to produce
a coherent vision of unmanned vehicles
• Design a Command and Control (C2)
architecture considering potential technology
gaps and determine a more streamlined
architecture with gap fillers
2
Current C2 Process
Operator
Mission
Controller
Sensor feed
Execution approval
Limited telemetry
Mission Tasking Order
Mission
Controller
Sensor feed
Execution-approval
Telemetry
Mission Tasking Order
Manned-System
Sensor feed
Actuator-control
Telemetry
Navigation Control
Display &
Control
Display &
Control
Sensor feed
Display &
Actuator-control Control
Onboard
Telemetry
Display &
AI
Control
Navigation Control
Local
Sensor &
Actuator
Platform
Local
Sensor &
Actuator
Platform
Unmanned System (Autonomous)
3
Conceptual Logic of
2030 C2 Process
Operator
Sensor feed
Actuator-control
Telemetry
Navigation Control
Display &
Control
Local
Sensor &
Actuator
Display &
Control
Platform
Manned-System
Sensor feed
Sensor feed
Sensor feed
Mission
Controller
C2 Capability Gap
Sensor feeds
Mission Tasking Order
Display &
Sensor
Display
&
Control
OnSensor
Display
&
Control Sensor
Onboard
Control
OnTelemetry
board
Display &
Telemetry
Platform
boardAI AI
Display
&
Control
Telemetry
Platform
Navigation &Display
&
AI
Control
Platform
Navigation
&
Flight
Control
Control
Navigation &
Decision 1 Flight Control
Decision 1 Flight Control
Unmanned Sensor Systems
Sensor feeds
Execution approval
Telemetry
Mission Tasking Order
Sensor feed
Sensor feed
Sensor
Display &
Sensor
&
Fire-control Display
Control
On-Sensor feed
Local Actuator
Control
&
On-board Fire-control Display
Actuator
Sensor
&
Telemetry
Actuator-control
ControlDisplayActuator
&
On-boardAI
Telemetry
Platform
Display
&
Control
board AI
Platform
NavigationDisplay
& Control
Telemetry
&
AI
Navigation
&
Platform
Flight Control
Control
Flight
Control
Navigation
&
Decision 1
Decision 1 Flight Control
Unmanned Actuator Systems
Common Picture Gap
Common Interface Gap
4
Air
Space
Self-Forming /
Self-healing
Sea
Self Protection
High Computing Power
Collaboration Net
INTRANET
Land
Conditional Self
Appointed Master
Swarm Behavior
Under Sea
Manned and
Unmanned Units
5
Human and Machine Comparison
6
Source: Canning, John S. “A Definitive Work on Factors Impacting the Arming of Unmanned Vehicles” NSWC Dahlgren
Autonomous Levels for Unmanned Systems
Reference: National Institute of Standards and Technology
• high level Human-Robot
Interaction (HRI)
• low level tactical
100
behavior
%
• simple environment
HRI
0%
HRI
• low level HRI
• collaborative, high
complexity missions
• difficult environment
• mid level HRI
• mid complexity, multifunctional missions
• moderate environment
10
0
1
2
Low
Remote
control
3
4
5
Medium
Autonomy Level
6
7
8
9
High
Full, intelligent
7
autonomy
Functional Architecture
0Manage UV Operations
1 Provide C2
1.1 Observe
1.1.1 Monitor Situation
1.1.1.1 Monitor Internal Factors
1.1.1.2 Monitor External Factors
1.2 Orient
1.2.1 Understand Situation
1.2.1.1 Assess Friendly Capability
1.2.1.2 Assess Threat
1.2.1.3 Analyze Environment
1.2.2 Identify Mission Success Gap
1.3 Decide
1.3.1 Determine COA
1.3.1.1 Develop COA
1.3.1.2 Analyze COA
1.3.1.2.1 Assess Risk
1.3.1.2.2 Analyze timing
1.3.1.2.3 Select COA
1.4 Act
1.4.1 Command Assets
1.4.1.1 Assign Mission
1.4.1.2 Direct UVs
1.4.1.3 Provide Resources
1.5 Share to Network
2 Collaborate
2.1 Operate in Network
2.1.1 Establish Capability Interface
2.2 Manage Data
2.2.1 Organize Data
2.2.2 Share Data
2.3 Collect Data
2.4 Secure Network
3 Conduct UV Operations
3.1 Operate Sensors
3.1.1 Sense Environment
3.1.2 Share Raw Sensor Data
3.1.3 Fuse Sensors
3.1.4 Share Sensor Picture
3.2 Operate UVs
3.2.1 Formulate Tactics
3.2.2 Schedule and Allocate Tasks
3.2.3 Navigate/Execute Task
3.2.4 Report Position/Status
3.2.5 Assess/Report Operational Availability
8
Operational Node Connectivity
(Subordinate)
9
C2 Information Exchange
Headquarters
(HQ)
Command
Recognized
Picture
Sensor Feed
Telemetry
Report
Request
Sensor Feed
Sensor Feed
Manned
System (MS)
Command
Payload Control
Sensor Feed
Telemetry
Report
Request
Command
Payload Control
Conditionally
Self-appointed Master
Available
Master
Unmanned Vehicle (UV)
10
Manned System/UV(Master) to HQ
Category
Info Type
Data Type
Bandwidth
Timeliness
Sensor
Feed
EO/Video Camera
Video (Live)
High
Milliseconds
Radar
Data (Tracks)
Low
Seconds
Triggering
Events
- Algorithm
- Operator
- Time
As above
SAR/ISAR
Image
Mid
Minutes
As above
IA
Optional – C
Gamma Radiation
Image
Mid
Minutes
As above
IA
Terra-Hertz
Image
Mid
Minutes
As above
IA
IFF
Data (Tracks)
Low
Seconds
As above
IA
Sonar
Data (Tracks)
Audio
Data
Low
Mid
As above
IA
Low
Seconds
Milliseconds
Variable
As above
IA
Data
Low
Minutes
As above
A
Data
Low
Minutes
As above
IA
Data
Low
Seconds
- Algorithm
Telemetry
Report
On-board
Instrumentation
BIT Status
Request
AI Decision
Feedback
Execution
CIA
IA
Optional – C
CIA
CIA
11
Operational Activity Model
Collaboration Net
External Sensors
UV
OV-5 - Force Protection
Sense
Environment
* Assess
Friendly
Capability
* Assess Threat
* Analyze
Environment
Sensor Feeds
Assets &
Threats
* Develop COA
* Assess Risk
* Analyze Time
Criticality
* Select COA
* Assign
Mission
Navigate /
Execute
Mission
Task
Task
Status
Assets &
Threats
Update
Task Status
Update
Task Status
Sense
Environment
Status
Update
Publish Assets
& Threats
Information
Tasking Orders /
Manual Control Messages
Receive
Asset &
Threats
Information
Receive
Task Status
Update
Publish
Task Status
Update
Status
Update
Assets &
Threats
HQ
Tasking
Orders
Plan & Send
Tasking Order /
Control Drone
Receive Task
Status Update
12
Conceptual System View
Security
Infrastructure
Operating
Systems &
COTS
Space
Management
Target
Management
Operation
Management
Shooter
Management
BDA
Management
Frequency
Management
Resource
Management
Data Fusion
Time & Space
Analysis
GIS
Services
Identification
Engine
Time
Management
Medical
Notification
Intel
Assessment
Tracks
Geographical
Data
Weather
Imagery
Logistics
Manpower
Knowledge
Bases
Replay
Engine
Process Monitoring
Authentication &
Authorisation
Confidentiality
Message Delivery
Message Transformation
Message Mgmt
Integrity
Platform Service Adapter
Data Service Adapter
Web Service
Non-Repudiation
Encryption
Sensor
Management
Service Lookup
Directory
Business Process
Execution
Campaign
Management
Connectors
Service
Infrastructure
ORBAT
Enterprise
Service Bus
Data
Services
Common
Situation Pic
Process
Engine
Enterprise
Applications
Service Registration
Service Directory
Security Administration
System Monitoring
Business
Business
ProcessProcess
Engine Operations
Rules Engine
Communication Package
Collaboration Package
Messaging Package
Timer Function
Backup and Recovery
Data Storage Package
13
Global Hawk and Predator Analysis
Coverage Area (nm2)
Combat Radius (nm)
Endurance (hr)
2010
2020
2030
2010
2020
2030
2010
2020
2030
RQ-4 Global
Hawk
5400
5940
6210
9.16E+07
1.11E+08
1.21E+08
36
39.6
41.4
MQ-1
Predator
500
550
575
7.85E+05
9.50E+05
1.04E+06
40
44
46
Expected Endurance Increases
Engine Cycle Only
Endurance (hrs)
50
Breguet Range Equation
40
30
20
RQ-4 Global Hawk
10
MQ-1 Predator
0
2000
2010
2020
Year
2030
2040
Fixed Platform Assumptions:
V , g = constant
Structural/Tank mass = constant
14
Discrete Event Model
(i<k+1)
Run
Init
(i)
{P=P-1}
Failure
(R1<fT)
Start
fT
(u)
Repair
u
u
(u)
{ u.reset( ),
(R2<Pt)
s.add(u)}
u
u
R1
R2
(R1>fT)
fT
Create
Launch
Start
Patrol
u
Pt - fT
TD = getSimTime()}
{P=P+1}
(u)
Pt
{ u=s.removeFirst()
{ u=new UAV,
Repair
(u)
{ R=R+1}
(s.isEmpty())
End
tr
u
(R2>Pt)
s.add(u),
(R2>Pt)
M=M+1 }
End
Patrol
(u)
{P=P-1}
Start Turnaround
fT
u
tm
(u)
{Tclocked += getSimTime() - TD}
u
End Turnaround
(u)
{s.add(u)}
15
Scenario Analysis: Current Limits
Threat Detection
Range
Timeline Analysis
Distance
Mach 4+ Anti-Ship
Missiles
A
2nd
Engagement
Impossible!
C
B
D
Time
Reaction
Time
(10-15 sec)
A: Detection of Enemy Missile
B: Launch of Anti Missile Missile
C: AMM intercepts Enemy Missile
D: Enemy Missile reaches target
16
Distance
Extended Detection Ring
Extended
Detection Ring
A*
2 engagements
now possible
with early
detection
Mach 4+ Anti-Ship
Missiles
C*
C
B*
B
D
Time
Reaction
Time
(10-15 sec)
17
Solution Analysis
Coverage Overlap
(1-4 sec)
C2 Architecture enables a
group of UAVs to collaborate
and fly together
Questions for Analysis:
1) What is the number of aerial
picket stations required?
Range
(30±10 km)
Platform: Mid-Altitude UAVs
Sensor: Side-scan Doppler
Radar
2) Size of UAV fleet required,
given logistic constraints.
Primary Considerations:
- Endurance
- Platform / Sensor mission
critical failures
- Radar Range
- Coverage Overlap
18
Modeling and Results
• Number of Aerial Picket Stations modeled by
geometry
• Determination of Fleet size modeled as a
Scheduling problem with Discrete Event Simulation
• Monte Carlo simulation (1000 runs) using SimKit
Flight to
Station
UAV 2
UAV 1
Time on Station
Time on Station
Flight to
Base
Turnaround
+ Repair
Variables
40hrs
43hrs
Time
19
Modeling and Results
• A baseline fleet size of 21 UAVs is required
• A conservative estimate is 35 UAVs
Fleet Size
Variation of Fleet Size with Detection
Range and Coverage Overlap
40.0
30.0
Fleet Size 20.0
10.0
0.0
4
20
2
Detection Range
30
(km)
1
40
Coverage
Overlap
(sec)
Detection Range (km)
Coverage
Overlap
(sec)
20
30
40
1
30
21
18
2
31
22
18
4
35
24
19
20
Estimation of BW requirement
Sensor
Detection
zone 4
missile
• Estimated number of units
supportable per datalink net:
reserved for sensor data transmission
n <  2 ×Capacity

M × Datarate demand per unit per track detected 

<
4




 2× M ×8




Cb (bit / s)

(bit / byte) × D(byte / track ) ×T (track / s) 

5
3
6
2
C2 Centre
7
1
•D: Average data size per track (bytes/track)
•T: Track update rate (tracks/second/target)
•Cb: System throughput capacity (coded)
reserved for Link-16 sensor feed format
(bits/sec)
•M: Max number of concurrent missile attacks
expected
• Number of datalink nets required:
N
8
…………..
Net1





N
f ≈ n 


21
Range Extension
Two-tier relay network
• NET0
• Tactical Datalink; or
• BLOS Comms (e.g. SATCOM)
Net1
Net M
Net2
4
3
5
Net3
6
22
C2 Centre
7
Net4
Link Budget: Link-16 (UHF-LOS)
Fade
Margin
=
E 
 b=

N 
 0

received
E 
 b


 N0 

received
 R 

b 
S=
 kT



sys




Lchannel =  4π f c R 
c 

E 
−  b 
 N0 

min
Pt .Gt .Gr  Rb 
Lchannel .Lsys  kTsys 


2
Assumptions
• RF carrier frequency, fc = 1215MHz. (Link-16 Max frequency for UHF-LOS band)
• Receiver system noise temperature of, Tsys = 410K;
• Channel Bit-rate, Rb = 2400bps;
• Omni directional antennas with gain, Gt, Gr = 1dBi;
• Transmitter Power, Pt = 10W, 20W, 50W, 100W
• Digital Signal-to-Noise ratio (assume QPSK @ BER <10-5), Eb/N0, min ≈ 10dB (See Figure 2);
• Other system losses, Lsys = 3dB;
• Channel Loss Model: Free space path loss model;
• Boltzmann Constant, k = 1.38x10-23Joules
23
• Speed of Light, c = 3x108m/s
Range Assessment
Fade Margin (dB) Vs Range (km)
60.00
Fade Margin is based on Eb/N0 level above
threshold level to achieve BER < 10-5 for
QPSK modulation
Fade Margin (dB)
50.00
A higher fade margin value caters for more
reliable datalink under environment which
attenuates signal propagation
40.00
30.00
20.00
Pt=10W
Pt=20W
10.00
Pt=50W
Pt=100W
0.00
0
20
40
60
80
100
120
140
160
180
200
Distance (km)
24