ü From April 5 – 14, 2022 (2 Weeks, 4 Classes, 8 Lectures/Hours)
ü Every Tuesday
and Thursday at 1300-1500 Eastern Time (all
sessions will be recorded and available for replay; course notes will be
available for download)
ü All students will receive an AIAA Certificate of Completion at the end of the course
Overview
Learning Outcomes:
- Describe fundamental concepts of Data and Information Fusion
- Summarize and apply Multi-Level Reference Model of Data and Information Fusion
- Develop Networked and Distributed Sensor and Data Fusion
- Recognize Functional Issues and employ Mathematical Techniques
- Plan and execute Testing and Evaluation of Data Fusion Processes
- Perform Systems Engineering of Data Fusion-Enabled Systems
- Describe Aerospace Applications of Data and Information Fusion
Who Should Attend
This course is directed to
technical program managers, lead engineers, and graduate students who want to
get a first-level understanding of Data and Information Fusion both as a field
of study and from a systems development/application perspective as well.
Course Fees (Sign in to Register)
- AIAA Member Price: $595 USD
- Non-Member Price: $795 USD
- AIAA Student Member Price: $395 USD
Course Outline
- Lecture 1: History/Foundations, Reference Model, Terminology,
Multidisciplinary Aspects, The Profession, Breadth of Applications, Benefits
- Terminology and basic functional concepts
- Understanding Data & Information Fusion (DIF) as an Estimation process
- Appreciating the multidisciplinary nature of DIF
- Brief examples of applications in aerospace, disaster relief, condition-based maintenance
- Notions of the Cost-Benefit Tradespace
- Lecture 2: Understanding the Fusion Node Concept, involving Alignment/Common Referencing, Data Association, and Estimation
- The Fusion Node (FN) as the foundational component of all DIF architectures
- A sample of the DN in an example DIF architecture—and the Dual Node Network concept
- The crucial role of Data Association and the concept of its structure
Lecture 3: Functions & Architectures, Typical alternatives/tradeoffs, Distributed & Networked Architectures and Fusion Issues
- The Distributed Network setting for DIF operations
- Typical network topologies and tradeoffs
- Subtle yet critical issues: double counting; correlation effects
- Example application in Counter-Drone applications
Lecture 4: Representative Mathematical Flow and Issues; Multisensor Multiobject Tracking Example
- Using the Fusion Node idea to frame the approach
- Reviewing each functional component:
- Alignment: coordinate systems, uncertainty normalization
- Data Association: association hypotheses, scoring, optimization
- Estimation: Kalman Filtering and Variations
- Fusion: Information Matrix Fusion and Covariance Intersection
- Lecture 5: Introduction to High-level Data Fusion for Situational Awareness Tracking Example
- Brief introduction to Situational Awareness problem formulation and high-level data fusion
- Introduction to Bayesian Networks and Dempster-Schafer Theory for heterogeneous data fusion
- Hands-on
working examples with Bayesian Networks and Dempster-Schafer belief function
fusion
Lecture 6: Systems Engineering of Data Fusion Systems
- Brief Introduction to Engineering Complex Systems and System of Systems
- Systems Engineering Needs for Data Fusion Systems
- Functional, Physical, and Allocated Architectures of Data Fusion Systems
- Modeling,
Simulation, and Executable Architectures for Data Fusion Systems
Lecture 7: Testing and Evaluation of Fusion Processes
- Test and Evaluation Challenge for DIF Systems
- Trade space analysis, Experimental Design, and Machine Learning for Data Fusion Systems
- Machine
Learning Application Example for Distributed Target Tracking Test and
Evaluation
- Lecture 8: Aerospace Applications of Data and Information Fusion
- Aerospace Mission Concepts and the Role of DIF; Example application to include:
- Missile Defense and Command and Control (C2) Systems
- Autonomous Vehicles, Unmanned Aerial Systems (UAS) and Counter-UAS
- DIF for Space Debris Tracking
- Role of DIF in Space Exploration Missions
Dr. James Llinas brings over 35 years of experience in multisource
information processing and data fusion technology to his research, teaching,
and business development activities. He
is an internationally-recognized expert in sensor, data, and information
fusion, co-authored the first integrated book on Multisensor Data Fusion, and
has lectured internationally for over 20 years on this topic. His experience in applying this technology
to different problem areas ranges from defense applications to non-defense
applications to include intelligent transportation systems, medical
diagnostics, and condition-based maintenance, among others. Current research activities related to the
field of Information Fusion include funded programs in Space Situational
Awareness, Machine Understanding, Autonomy/Autonomous Operations, and Missile
Defense. He has been a Consultant to many U.S. and International defense
organizations to include the Air Force Research Laboratory, DARPA, NSA, and the
NRO.
Dr. Llinas created the concept for and is now Director for the “Center for Multisource Information Fusion” located at the State University of New York at Buffalo. This first-of-its-kind, University-based research center has been conducting basic research in Data and Information Fusion over some 20+ years.
Classroom hours / CEUs: 8 classroom hours / .8 CEU/PDH
Course Delivery and Materials
- The course classes will be delivered via Zoom. You can test your connection here: https://zoom.us/test
- Access to the Zoom classroom will be provided to registrants near the course start date.
- All slides will be available for download.. No part of these materials may be reproduced, distributed, or transmitted, unless for course participants. All rights reserved.
- Between lectures during the course, the instructors will be available via email for technical questions and comments.
Cancellation Policy: A refund less a $50.00 cancellation fee will be assessed for all cancellations made in writing prior to 10 days before the start of the event. After that time, no refunds will be provided.
Contact: Please contact Lisa Le or Customer Service if you have questions about the course or group discounts (for 5+ participants).