COURSE # ROO-411
AUTOMATIC TARGET RECOGNITION: PRINCIPLES, ALGORITHMS AND APPLICATIONS
A comprehensive review of ATR principles and the state-of-the-art techniques.
The application of automatic target recognition (ATR) technology is a critical element of electronic warfare (EW), advanced avionics and reconnaissance systems, smart weapons, and serial data interface (SDI). The success of ATR technology in the Persian Gulf war has made its continued development a top priority within the DoD. This course reviews fundamental image- and signal- processing techniques applicable to ATR systems. It discusses ATR architectures and critical components and their applications in the visible domain, millimeter wave (MMW) radar, laser radar, synthetic aperture radar (SAR), and other sensors. Concepts in designing and implementing ATR algorithms are covered, including signal enhancement and restoration, target detection and segmentation, motion analysis and tracking, statistical and model-based recognition, and phenomenological modeling. Included in this discussion are multisensor and information fusion algorithms and ATR performance evaluation. The course describes in detail model-based ATR, adaptive systems, and applications of artificial intelligence (AI) and neural networks in ATR. Additional topics address the limitations of current generation technology and selected advanced concepts for next generation ATR systems. The course concludes with a discussion of hardware architectures and market trends.
Applications and benefits:
You will benefit by enhancing your understanding of the :
- Current ATR systems, algorithms, sensors and architectures.
- Techniques for designing, developing, and evaluating next-generation ATR algorithms and
systems.
- Evolving ATR technology and market trends.
Who should attend:
This course introduces the principles, techniques and algorithms used in Automatic Target Recognition. The material covered should serve as an invaluable resource for managers, system analysts, engineers and designers engaged in the design or analysis of ATR systems for military or industrial applications. Business development and marketing personnel who need a primer in ATR technology will find it most informative. This course has no prerequisites; however, a background in engineering, science, or equivalent experience will be helpful.
Course Outline:
- Review of basic ATR concepts and requirements
- Historic perspective of ATR technology evolution
- Military mission requirements
- Basic components of an ATR system
- Review of current capabilities
- Laser and MMW radar
- SAR
- Other sensors
- Trade-offs
- Principles of phenomenological modeling
- The science of ATR
- Sensor modeling
- Target signature and background modeling
- Effects of environmental factors on target signatures
- Target detection
- Feature-based techniques
- Silhouette-based techniques
- Clutter rejection
- Segmentation
- Target and scene segmentation
- Model-based techniques
- Description of the state-of-the-art algorithms
- Target tracking
- Motion detection techniques
- Kalman filters
- Optical correlators
- Feature tracking
- Optical flow
- Scene transformation and registration
- Comparing different techniques
- Multitarget tracking
- Target recognition
- 2- and 3-D representation
- Hybrid methods
- Matching
- Statistical approaches
- Silhouette and 2-D matching
- 3-D matching
- Relaxation, decision-tree and graph-theoretic approaches
- Multisensor ATR systems
- Motivation
- Forward-looking infrared (FLIR), radar, laser radar (LADAR), SAR, and television systems
- Multisensor fusion techniques
- Applying AI and neural networks to ATR systems
- Limitations of current systems
- AI techniques for ATR applications
- Knowledge-based ATR architectures
- Scene understanding
- Knowledge-based segmentation and system control
- Information fusion
- Neural networks for ATR: learning and adaptive systems
- Model-based ATR
- Motivation
- Target, sensor, environment modeling
- Model-based system approaches
- Issues in model-based approaches
- ATR system evaluation
- Performance evaluation
- Sensor evaluation
- Algorithm evaluation
- Ground-truthing and image-truthing
- Advanced concepts
- Hardware architectures
- Basic concepts
- Different architectures
- Algorithm mapping
- Test beds
- Real-time systems
- Trends and markets in ATR
- Key players in the ATR business
- ATR DoD centers
- ATR funding and programs
- Market prospects
Text: Computer Vision, by Bellard and Brown; Prentice-Hall
About the Instructor
Hatem N. Nasr is a senior principal research scientist at Honeywell Systems and Research Center, where he specializes in advanced concepts an applications for single- and multisensor ATR systems. Mr. Nasr has been a program manager and principal investigator for a variety of defense projects and a consultant to NASA. He has served as a chairman and co-chairman of several international conferences.. Mr. Nasr is the editor of two books and co-author of a book on ATR. He holds one patent and has received several awards including the Honeywell Technical Achievement Award.
Mr. Nasr holds an M.S. in systems engineering from the University of Houston, Tx.
Details:
Course: ROO-411 Duration: 3 Days FEE: $1,195 CEUs: 2.16
Please direct any additional inquiries regarding this course to Robert Blakely, Program Director, by e-mail, FAX: (301) 871-4942 or TELEPHONE: (301) 871-9608.
Call toll free 1-800-683-7267 from anywhere in the Continental U.S. or CANADA.
Last modified December 12, 1997.
