Published on IST 885: Introduction to Multisensor Data Fusion (https://online.ist.psu.edu/ist885hall)
Course Information
Introduction to Multisensor Data Fusion
Instructor Information
Dr. Ben Hellar
Hello students! My name is David Benjamin Hellar, and I am the Instructor for this online section. I
am also a proud alumni of the Penn State IST program, having graduated in 2004 with my Bachelors
Degree and 2009 with my Doctorate. Like many of you in the course, I have a full life outside of
academia. In my professional career outside of teaching, I work full-time as a Senior Usability
Engineer for the Next Century Corporation, a small government contractor based around Columbia,
Maryland. There I design and architect interfaces for large data fusion and knowledge management
systems used by the Department of Defense. As a result, I am not always available for email during
daytime EST hours, and will often respond after work hours, commonly from 6 PM - Midnight ET.
In my personal life, I am married with a young baby, both of whom are thankfully beginning to sleep
through the night :) When I'm not chasing around family, you can usually find me chasing around
my fur baby, a wheaton terrier, who often thinks she's human. With what precious time I have left
after that I enjoy Microbrew and Belgian Beer and try to squeeze in the occasional video game here
and there.
One more thing. Although my first name is David, I go by my middle name Benjamin, and thus you
may see emails come across signed as either David Hellar or D. Benjamin Hellar If at anytime you
feel stuck or have questions regarding the material or due dates, please don't hesitate to ask and
email me at through ANGEL.
Education
Ph.D., IST, The Pennsylvania State University
B.S., IST, The Pennsylvania State University
Contact Information
E-mail: bhellar@ist.psu.edu [1] - Use ANGEL first before emailing me directly!
Online Office Hours: Available by appt only
Office number: 443-545-3139
About ANGEL
ANGEL is a web-based tool to help you access and manage your courses at Penn State. ANGEL
enables you to view and save course materials, participate in online discussions and chats, share
files, easily communicate with faculty and other students, check your grades and lots more!
Accessing Your Courses with ANGEL
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Access ANGEL from any computer with an Internet connection.
Use Internet Explorer or Firefox to go to http://cms.psu.edu [2]
Click <Log On> and enter your Access Account User ID and password
Your Profile page is displayed with links to tools and to your ANGEL courses and groups.
Editing Personal Information and Forwarding ANGEL Email
Edit your ANGEL personal information by clicking <Preferences> from any page in ANGEL. Then,
click on <Personal Information> and enter your information.
ANGEL mail is separate from your Penn State email. To make sure you don’t miss any messages, you
can set up ANGEL email forwarding by clicking <Preferences>, then <System Settings>. Scroll
down, enter your Penn State email address, and change the forwarding settings. Click <Save>.
Navigating within a Course
From your Profile page, click on the course you want to work with.
The Lessons tab will open automatically. This is where most of the course materials are
found.
The Communicate tab provides access to course mail, chat tools, and the roster.
The Report tab provides information about your ANGEL activity, attendance and grade
information.
The Resources tab provides access to library reserves and other course resources. All items
in the library reserves are named exactly as they appear on the Roadmaps and are in
ALPHABETICAL order.
The Calendar and Syllabus tabs are self-explanatory!
Getting Help
Click <Help> from any screen within ANGEL for extensive "how to" information. Access the "Quick
Start Guide for Students" from the Help screen by clicking <Student Topics> in the list on the left.
Logging Off
When you are finished using ANGEL, click <Log Off> on the left side of the screen. Logging off
ensures that your activity will be accurately logged within ANGEL.
About PSU Web Apps
What are Penn State WebApps and WebFiles?
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[3]
WebApps and WebFiles are two related services that give you access to a number of applications
licensed by Penn State. All you need is a modern browser. These services can be accessed from
desktop and mobile browser versions. Now you can do desktop-level computing from your iPad or
other tablet device!
WebApps allows you to use your Penn State Access ID to use dozens of applications without
installing any software on your local or mobile computer. These are fully-featured applications and
will allow you to do practically anything you would in a standard installation environment.
WebFiles complements WebApps by allowing you to easily upload, download, and manage your files.
Any file you would like to edit, needs to be uploaded to WebFiles before you launch WebApps.
See more: Supported Browsers and Available Applications [4]
To get started with WebApps, visit this URL: http://webapps.psu.edu/ [3]
To get srtated with WebFiles, visit this URL: https://webfiles.psu.edu/ [5]
See more: Printing Tips [6] and iPad Tips [7]
For even more great tips, visit ITS's WebApps page [4]
Where can you go for more help?
1. Ask your fellow classmates, team members and faculty team in the Question Cafe discussion
forum in ANGEL.
2. Reset your stored profile [8] on the server.
3. Technical problems? Contact the World Campus Technical Support [9].
4. Find info from our very own Penn State ITS [4] group.
v1.1 - 7/15/13
Academic Integrity
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Academic Integrity, according to the Penn State Principles and
University Code of Conduct, is:
"A basic guiding principle for all academic activity at Penn State University, allowing the pursuit of
scholarly activity in an open, honest, and responsible manner. In according with the University’s
Code of Conduct, you must not engage in or tolerate academic dishonesty. This includes, but is not
limited to cheating, plagiarism, fabrication of information or citations, facilitating acts of academic
dishonesty by others, unauthorized possession of examinations, submitting work of another person,
or work previously used without informing the instructor, or tampering with the academic work of
other students."
The College of IST is committed to maintaining academic integrity in this and all other courses it
offers. IST takes academic integrity matters seriously. Academic integrity - scholarship free of fraud
and deception - is an important educational objective of Penn State. Academic dishonesty can lead
to a failing grade or referral to the Office of Judicial Affairs [10]. Academic dishonesty includes, but is
not limited to:
cheating
plagiarism
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fabrication of information or citations
facilitating acts of academic dishonesty by others
unauthorized prior possession of examinations
submitting the work of another person or work previously used without informing the
instructor and securing written approval
tampering with the academic work of other students
In cases where academic integrity is questioned, Penn State's policy on academic integrity [11]
requires that the instructor give the student notice of the charge as well as the recommended
sanction. Procedures allow the student to accept or contest the charge through discussions with the
instructor. If a student chooses to contest, the case will then be managed by the respective College
or Campus Academic Integrity Committee. If a disciplinary sanction also is recommended, the case
will be referred to the Office of Judicial Affairs [10].
All Penn State colleges abide by this Penn State policy, but review procedures vary by college when
academic dishonesty is suspected. Information about Penn State's academic integrity policy and
college review procedures is included in the information students receive upon enrolling in a course.
Additionally, students enrolled at Penn State are expected to act with civility and personal integrity;
respect other students' dignity, rights, and property; and help create and maintain an environment
in which all can succeed through the fruits of their own efforts. An environment of academic integrity
is requisite to respect for self and others, and a civil community.
For more information on academic integrity at Penn State, please visit one of the following URLs:
http://www.psu.edu/dept/oue/aappm/G-9.html [12]
http://www.sa.psu.edu/ja/ [10]
Course Outline
Topic
Topic
Topic
Topic
Topic
Topic
Topic
Topic
Topic
Topic
Topic
Topic
Topic
Topic
Topic
Topic
Topic
1: Introduction
2: The JDL Model
3: Project
4: Sensors
5: Level 0
6: Level 1 Correlation
7: Level 1 Estimation
8: Level 1 Identification
9: System Engineering
10: Project
11: Level 2
12: Level 3
13: Level 4
14: Level 5
15: Project
16: State-of-the-Art
17: Final Presentations
Success Outline
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Online students face as many challenges as resident students, if not more.
Things to think about with an eye towards success:
Know Thy Course
There is a difference between wanting to take a course and having to take a course.
Think about why you are taking the course. What are your objectives and goals? Being
specific about your outcomes reinforces your motivation and will help you to learn.
Conversely, think about what is expected of you as part of the course. How will you be
graded or assessed? How much time are you expected to spend on the course? By knowing
what is expected of you, you can plan your learning strategy or strategies appropriately.
The syllabus is your bible. The syllabus should outline all expectations, due dates, and
requirements of the course. The syllabus is your map through the course and to your
success!
Do you meet the minimum requirements for the course, and if you do not, can you develop
yourself to meet those requirements? Do you want to?
Manage Time Appropriately
Most online courses may take from 5 to 15 hours of your week. To fit this time in, you must plan for
it.
Keep a calendar indicating due dates for assignments and tests and do not turn in anything
late.
Mark up, highlight, and dog-ear your syllabus.
Set up a study schedule and stick to it! Get your family and friends on board to support you.
Log-in to your course and check your emails daily to stay on top of potential changes or
receive any breaking news.
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Participate
You paid for the course, now become a part of it!
Communicate with your instructor and your peers using email, instant messaging, and any
other tools that you feel can aid in becoming part of your course community.
Check your email frequently.
Be polite and respectful to individuals in your course community.
Ask questions.
Attend any online meetings whether you have questions or not.
If you can't make a deadline or are going to miss an assignment, talk to the instructor!
Learn
Share your eductational, occupational, and life experiences with your peers beyond the
classroom.
Develop your writing skills.
Be yourSELF--self-motivated, self-disciplined, self-directed.
Think critically and make informed decisions.
Share, explore, and discuss ideas.
Be open.
Keep up with technology and the tools required by the course.
Enjoy
If you aren't enjoying the time you are spending with your course, then maybe the course is not for
you. Or maybe you are not meant to take the course online. Online learning requires a large amount
of motivation and dedication by the learner. As an online learner, you must be proactive and make
the most of your learning. You paid for it. You might as well make the most of it.
Additional Resources
If you have any questions or concerns with your course and its content, please contact your
instructor.
If you have any questions or concerns regarding technical issues, contact the World Campus
technical support staff.
Illinois Online Network: Educational Resources [13]
About Blackboard Collaborate
What is Blackboard Collaborate?
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[14]
Bb Collaborate is a collaborative tool that allows you to communicate synchronously (real-time) with
your instructor and classmates. The software package allows real-time voice, document and
whiteboard sharing, among other things. It is also possible to record Collaborate sessions for viewing
at a later time. It is very similiar to Adobe Connect.
This course provides Collaborate as a tool to meet up with your:
instructor(s) for office hours and tutoring sessions
fellow team members for working on team projects, etc.
Please visit the World Campus FAQ [15] for more information.
Requesting your own Bb Collaborate room for team assignments
Click on this link to request a room for your team or for yourself [16] (24-hr turn around).
Bb Collaborate vs. Adobe Connect
You may be familiar with Adobe Connect. Bb Collaborate provides a similar feature set. We have
recently switched to Collaborate. One of the reasons we have made a switch to Collaborate is that
many other World Campus courses already use this tool. We fully support Collaborate, so please
contact World Campus Helpdesk with any technical problems.
The biggest difference is that you will now apply for your own Collaborate room whereas we would
create Adobe Connect spaces for each team in the past. Please use the link above to request your
own room.
Have you tried Bb Collaborate yet?
If this is your first time using Collaborate, please visit the website to Test Your Configuration [17].
Collaborate will automatically check your operating system and inform you if you need to download
the client. If you need to download the client, follow the steps for first time users.
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We also encourage you to access the Online Orientation [18] on this site as well. This will ensure that
you are up and running for our online sessions.
What additional equipment do I need to participate?
Speakers and a microphone are key in being able to use Collaborate to its fullest. We recommend a
headset with a mic.
What are the minimum computer requirements?
Before you can get started in a Collaborate session, you should ensure that your computer is able to
support the needs of the environment. Your computer and browser should meet or exceed
these System Requirements. [19]
Where can you go for more help?
1. Ask your fellow classmates, team members and faculty team in the Question Cafe (or Classwide Discussion Board) discussion forum in ANGEL.
2. Technical problems? Contact the World Campus Technical Support [9]
3. Go to the source... Blackboard.com [20] for videos and a lot more!
If you need technical help, contact World Campus Technical Support here:
http://student.worldcampus.psu.edu/technical-support [21] or here: World Campus Helpdesk [9].
Sample Syllabus
IST 885: Introduction to MultiSensor Data Fusion
This sample syllabus is intended to show students the basic content and expectations of this course.
As a sample, all details are subject to change, so actual course content may vary.
Description
This course provides an introduction to multisensor information fusion. Multisensor information
fusion seeks to combine information from multiple sensors and sources to achieve inferences that
are not feasible from a single sensor or source. The proliferation of micro and nano-scale sensors,
wireless communication, and ubiquitous computing enables the assembly of information from
sensors, models, and human input for a wide variety of applications such as environmental
monitoring, crisis management, medical diagnosis, monitoring and control of manufacturing
processes, and intelligent buildings. This course will help students understand the concepts,
techniques and issues associated with developing and using multisensor data fusion systems. The
course will provide a combination of background information (via readings from the textbook and
selected papers), links to resource materials for current and future study via a special web site, and
practical experience in understanding an application and designing a conceptual data fusion system.
For those students who are not mathematically inclined, the course will provide an introduction to
techniques by describing the concept of the methods and an understanding of how they work. For
students who have an interest and background in applied mathematics, the course will provide
references to resources to show actual equations and algorithms. However, this mathematical
understanding will not be necessary to successfully complete the course.
Prerequisites
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None
Objectives
By the end of this course, you should be able to:
Explain different models of multisensor data fusion
Describe the six levels of data fusion in the Joint Directors of Laboratories (JDL) data fusion
model
Identify various techniques used in multisensor data fusion ranging from pattern recognition
and statistical estimation to automated reasoning.
Analyze a data fusion application (such as for environmental monitoring) and assess the
types of sensor and other input data, the required inferences and decision timeline, identify
fusion needs and challenges, and develop a functional design for a fusion system to address
the application
Articulate the advantages and limitations of data fusion
Describe the role of the human in the loop analysts/decision-maker in a fusion system
Assignments & Grading
The course will be graded in accordance with the following assignments and rubric.
The tables below summarize the individual and group assignments, evaluation criteria and weights,
together totaling 1000 points:
Individual assignments and evaluation (71 % of total grade) Assign # of
Evalu Points Total
ments Cours
e Assi
gnme
nts
Group Term Project (29% of total grade) Assignme
nts
T-1
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ation
per As Points
Criteri signm
a
ent
Quizzes -- Low
stakes quizzes
10 quizzes
Number
answers
Discussion
Activities /
participation
6 formal online
discussions
Quality
quality o
discussi
via discu
board
Writing
Assignments /
Individual minipapers
8 individual
writing
assignments
Focus, c
applicab
assigne
clarity, g
compos
referenc
Peer evaluation
1 at end of
semester
Evaluati
group m
your lev
quality o
participa
group p
# of
Evaluation Points per Total
Course As Criteria
Assignme Points
signments
nt
1 of 7 parts
Discussion Forum
post including
Page 10 of 18
10 pts
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Assignments
# of Course
Assignments
Evaluation Criteria Points per
Assignment
Total Points
name of team and
name of team
members
T-2
1 of 7 parts
Select a Data
20 pts
Fusion application,
develop an initial
briefing including
team name and
members,
identification of
application, initial
identification of
team member
roles, summary of
team experience
(as it relates to
the selected
application)
T-3
1 of 7 parts
For your selected
application,
provide summary
table of the
anticipated
information
sources and
sensors, type of
data, data rate,
data format, and
characteristics of
sensors/sources
T-4
1 of 7 parts
Definition, initial
40 pts
concept definition,
initial description
of functions the
fusion system
would perform
T-5
1 of 7 parts
First draft of final
written report
describing the
data fusion
system design
40 pts
T-6
1 of 7 parts
Final written
report
100 pts
T-7
1 of 7 parts
Final PowerPoint
presentation
50 pts
Course Grading Breakdown Grading Category
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30 pts
Percentage of Final Grade
Total Points
Individual Assignments
71%
710
Group Project
29%
290
Totals
100%
1000
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Course Grading Scale Grade
Percent
A
A-
B+
B
B-
C+
C
93% to
100%
90% to
92.9%
87% to
89.9%
83% to
86.9%
80% to
82.9%
77% to
79.9%
70% to
76.9%
Schedule
This sample schedule is subject to change, so actual course content may vary. Depending on the
semester in which you are enrolled, your course may be either 12 or 15 weeks long, not including
any breaks.The following schedule outlines the topics covered in this course, along with the
approximate time frames and activities.
Week 1
Week 1 Topic(s) Lesson 1: Introduction
Readings
Hall, D. L., and McMullen, S. A. H. (2004).
Mathematical Techniques in Multisensor
Data Fusion. 2nd Ed. Boston, MA: Artech
House. Chapter 1.
Topic 1 online materials
PowerPoint Presentation: Topic 1
Activities
Review of the syllabus
Watch Video Lecture: 01
Assignments
Week 2
Writing assignment 1 (W-1)
Team Assignment 1 (T-1)
Week 2 Topic(s) Topic 2: JDL Model
Topic 3: Project
Readings
Hall, D. L., and McMullen, S. A. H. (2004).
Mathematical Techniques in Multisensor
Data Fusion. 2nd Ed. Boston, MA: Artech
House. Chapter 2.
Hall, D. L., Hellar, B., Llinas, J. and
McNeese, M. (2007, June), “Assessing the
JDL model: a survey and analysis of
decision and cognitive process models
and comparison with the JDL model, in
Proceedings of the 2007 MSS National
Symposium on Sensor and Data Fusion
(NSSDF)
Topic 2 online materials
PowerPoint Presentation: Topic 2
Hall, D. L., and McMullen, S. A. H. (2004).
Mathematical Techniques in Multisensor
Data Fusion. 2nd Ed. Boston, MA: Artech
House. Chapter 11.
Topic 3 online materials
PowerPoint Presentation: Topic 3
Activities
Quiz 1
Introduction to the design project
"Meet" with your team and select one of
the data fusion application problems
Watch Video Lecture: 02 and 03
Assignments
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Writing assignment 2 (W-2)
Discussion 1 (D-1)
Team assignment 2 (T-2)
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D
60%
69.9
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Week 3
Week 3 Topic(s) Topic 4: Sensors
Topic 5: Level 0
Readings
Knies, R. (2008), “Sensor map delivers
real-time data on the go,” Microsoft
Research News and Highlights. [22]
Gilbey, J. “It never rains in VR” (science
fiction story in the collection, Futures
from Nature, edited by H. Gee, 2007).
Cuff, D. M. Hansen, and J. Kin, “Urban
sensing: out of the woods,”,
Communications of the ACM, March
2008, Vol. 51, No. 3, pp 24 - 33
Topic 4 online materials
PowerPoint Presentation: Topic 4
Farid, H., “Digital image forensics”,
Scientific American magazine, June 2008,
pp 66- 71.
Websites:
http://www.walterfendt.de/ph14e/dopplereff.htm
[23]
http://www.howstuffworks.com/no
ise-canceling-headphone.htm
[24]
http://video.esri.com/watch/1298/
imagery-and-lidar-datademonstrations [25]
http://wang.ist.psu.edu/IMAGE/
[26]
Topic 5 online materials
PowerPoint Presentation: Topic 5
Activities
Quiz 2: The JDL and related data fusion
process models
Explore the Sensor Map provided by
Microsoft at
http://atom.research.microsoft.com/sens
ormap/default.aspx [27]
Explore the web sites provided in the online materials
Watch Video Lecture: 04 and 05
Assignments
Week 4
Writing assignment 3 (W-3)
Discussion 2 (D-2)
Team assignment 3 (T-3)
Continue work on project
Week 4 Topic(s) Topic 6: Level 1 - Correlation
Topic 7: Level 1 - Estimation
Readings
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Hall, D. L., and McMullen, S. A. H. (2004).
Mathematical Techniques in Multisensor
Data Fusion. 2nd Ed. Boston, MA: Artech
House. Chapter 3.
Uhlmann, J. K. (1992). Algorithms for
multiple-target tracking. American
Scientist, 80(2), pp 128-141.
Topic 6 online materials
PowerPoint Presentation: Topic 6
Page 13 of 18
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Hall, D. L., and McMullen, S. A. H. (2004).
Mathematical Techniques in Multisensor
Data Fusion. 2nd Ed. Boston, MA: Artech
House. Chapter 4 pp 129 - 132.
Topic 7 online materials
PowerPoint Presentation: Topic 7
Activities
Assignments
Week 5
Visit the web sites provided in the on-line
materials
Writing assignment 4 (W-4)
Discussion 3 (D-3)
Week 5 Topic(s) Topic 8: Level 1 - Identification
Readings
Hall, D. L., and McMullen, S. A. H. (2004).
Mathematical Techniques in Multisensor
Data Fusion. 2nd Ed. Boston, MA: Artech
House. Chapter 5
See the web
site: http://wang.ist.psu.edu/IMAGE/
[26] for examples of pattern recognition
and labeling of pictures
Topic 8 online materials
PowerPoint Presentation: Topic 8
Activities
Quiz 5: Estimation and target tracking
Watch Video Lecture: 08
Assignments
Week 6
Quiz 3: Basic concepts in sensors and
level 0 processing
Quiz 4: Association and correlation
Meet (virtually) with your team and
define the types of entities that need to
be located, characterized and identified
for your selected fusion application
problem
Watch Video Lecture: 06 and 07
Visit the web sites provided in the on-line
materials
Writing assignment 5 (W-5)
Discussion 4 (D-4)
Week 6 Topic(s) Topic 9: System Engineering
Topic 10: Project
Readings
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Hall, D. L., and McMullen, S. A. H. (2004).
Mathematical Techniques in Multisensor
Data Fusion. 2nd Ed. Boston, MA: Artech
House. Chapter 10.
Bowman, C. L. and A. Steinberg, “A
systems engineering approach for
implementing data fusion systems,
chapter 16 in Handbook of Multisensor
Data Fusion, CRC Press, 2001, pp 16-1 –
16-39
Topic 9 online materials
PowerPoint Presentation: Topic 9
Hall, D. L., “The implementation of data
fusion systems, in Multisensor Fusion,
Page 14 of 18
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edited by A. K. Hyder, E. Shahbazian and
E. Waltz, NATO Science Series, Kluwer
Academic Publishers, pp 419 – 433
(2002).
Topic 10 online materials
PowerPoint Presentation: Topic 10
Activities
Assignments
Week 7
Continue to work on the project
Team assignment 4 (T-4)
Week 7 Topic(s) Topic 11: Level 2
Topic 12: Level 3
Readings
Hall, D. L., and McMullen, S. A. H. (2004).
Mathematical Techniques in Multisensor
Data Fusion. 2nd Ed. Boston, MA: Artech
House. Chapter 7.
Tutorials listed in online materials
Topic 11 online materials
Tutorial on rule-based systems;
see http://aidepot.com/Tutorial/RuleBased.html [28]
Tutorial on Bayesian Belief Nets,
see
http://dimacs.rutgers.edu/Workshops/Sur
veillance/slides/wong.ppt [29]
#260,1,Bayesian Networks: A Tutorial
PowerPoint Presentation: Topic 11
Wark, S. and D. Lambert, “Knowledgebased and artificial intelligence
systems”, chapter 11 in Concepts,
Models and Tools for Information Fusion,
edited by E. Bosse, J. Roy, and S. Wark,
Artech House, 2007, pp 279 – 309.
“The laws of truths and half-truths,”
chapter 2, pp 21-40 in The Drunkard’s
Walk: How Randomness Rules Our Lives,
by L. Mlidinow, Pantheon Books, 2008.
Topic 12 online materials
PowerPoint Presentation: Topic 12
Activities
Quiz 7: Systems engineering and
implementation issues
Quiz 8: Knowledge representation and
reasoning
Watch Video Lecture: 11 and 12
Assignments
Week 8
Quiz 6: Pattern recognition and target
identification
Team assignment: design of fusion
project – requirements definition &
analysis of system functions.
Watch Video Lecture: 09 and 10
Writing assignment 6 (W-6)
Discussion 5 (D-5)
Continue work on the project
Week 8 Topic(s) Topic 13: Level 4
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Week 9
Readings
Hall, D. L., and McMullen, S. A. H. (2004).
Mathematical Techniques in Multisensor
Data Fusion. 2nd Ed. Boston, MA: Artech
House. Chapter 8.
T. Mullen, V. Avasarala and D. L. Hall,
(2006) “Customer-Driven Sensor
Management,” IEEE Intelligent Systems:
Special Issue on Self-Management
through Self Organization in Information
Systems, 41-49, March/April 2006.
Topic 13 online materials
PowerPoint Presentation: Topic 13
Activities
Quiz 9: Automated reasoning
Watch Video Lecture: 13
Assignments
Writing assignment 7 (W-7)
Continue work on the project
Week 9 Topic(s) Topic 14: Level 5
Topic 15: Project
Readings
Hall, D. L., and McMullen, S. A. H. (2004).
Mathematical Techniques in Multisensor
Data Fusion. 2nd Ed. Boston, MA: Artech
House. Chapter 9.
Websites included in online materials
Web site on types of
displays: http://www.visual-literacy.org/p
eriodic_table/periodic_table.html [30]
Web site on visual
complexity
http://www.visualcomplexity.com/vc/
[31] .
Topic 14 online materials
PowerPoint Presentation: Topic 14
Antony, R., “Data management support
to tactical data fusion”, chapter 18 in
Handbook of Multisensor Data Fusion,
edited by D. Hall and J. Llinas, CRC Press,
2001 pp 18-1 – 18-25.
Topic 15 online materials
PowerPoint Presentation: Topic 15
Activities
Writing assignment 8 (W-8)
Quiz 10: Level 5 processing
Watch Video Lecture: 14 and 15
Assignments
Discussion 6 (D-6)
Week 10 Week 10 Topic(s) Topic 16: State-of-the-Art
Readings
Hall, D. and A. Steinberg, “Dirty secrets
in multisensor data fusion,” chapter 21 in
Handbook of Multisensor Data Fusion,
edited by D. Hall and J. Llinas, CRC Press,
2001, pp 21-1 – 21-12.
Topic 16 online materials
PowerPoint Presentation: Topic 16
Activities
Search for web sites that describe
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technology or related changes that could
impact your selected application
Watch Video Lecture: 16
Assignments
Week 11-13
Team assignment 5 (T-5)
Week 11-13 Topic 17: Final Presentation
Topic(s)
Readings
Topic 17 online materials
PowerPoint Presentation: Topic 17
Activities
Search for web sites that describe technology or
related changes that could impact your selected
application
Assignments Team assignment 6 (T-6)
Week 14-15
Week 14-15 Topic 17: Final Presentation
Topic(s)
Readings none
Activities
Assignments
Submit Final PowerPoint Presentation
Team assignment 7 (T-7)
Course Policies and Expectations
Logging into ANGEL - Students are expected to login regularly to check for course updates,
announcements, emails, discussions, etc.
Emailing through ANGEL - Students are expected to use ANGEL for all course email
communication.
Attending virtual meetings - Students are expected to use specified virtual meeting tool(s) for
collaboration, meetings, presentations, etc., as needed.
Source URL: https://online.ist.psu.edu/ist885hall/courseinfo
Links:
[1] mailto:bhellar@ist.psu.edu
[2] http://cms.psu.edu
[3] http://webapps.psu.edu/
[4] http://clc.its.psu.edu/UnivServices/WebApps
[5] https://webfiles.psu.edu/
[6] http://clc.its.psu.edu/UnivServices/WebApps/Printing
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[10] http://www.sa.psu.edu/ja/
[11] http://www.psu.edu/ufs/policies/47-00.html#49-20
[12] http://www.psu.edu/dept/oue/aappm/G-9.html
[13] http://www.ion.uillinois.edu/resources/tutorials/pedagogy/StudentProfile.asp
[14] https://meeting.psu.edu/
[15] https://courses.worldcampus.psu.edu/public/bbcollaborate/collaborateintro.html
[16] https://courses.worldcampus.psu.edu/public/roomrequest/index.php
[17] http://support.blackboardcollaborate.com/ics/support/default.asp?deptID=8336&amp;task=kno
wledge&amp;questionID=1473
[18] http://www.brainshark.com/blackboardinc/vu?pi=zGLzYw5XBz35Sgz0
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wledge&amp;questionID=1443
[20] http://www.blackboard.com/Platforms/Collaborate/Services/On-Demand-Learning-Center/WebConferencing.aspx
[21] http://student.worldcampus.psu.edu/technical-support
[22] http://research.microsoft.com/apps/catalog/default.aspx?t=news
[23] http://www.walter-fendt.de/ph14e/dopplereff.htm
[24] http://www.howstuffworks.com/noise-canceling-headphone.htm
[25] http://video.esri.com/watch/1298/imagery-and-lidar-data-demonstrations
[26] http://wang.ist.psu.edu/IMAGE/
[27] http://atom.research.microsoft.com/sensormap/default.aspx
[28] http://ai-depot.com/Tutorial/RuleBased.html
[29] http://dimacs.rutgers.edu/Workshops/Surveillance/slides/wong.ppt
[30] http://www.visual-literacy.org/periodic_table/periodic_table.html
[31] http://www.visualcomplexity.com/vc/
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