2004 IEEE Radar Conference

Innovative Radar Technologies - Expanding System Capabilities

 April 26-29, 2004 Wyndham Philadelphia at Franklin Plaza Philadelphia, Pennsylvania
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Tutorial 5.1
Radar Tracking and Track Filtering

Dr. Yaakov BarShalom - Univ. of Conneticut

Thu, 29 April 2004, 1:30 PM - 5:30 PM


Review of the Basic Techniques for Tracking. The Kalman, the Alpha-Beta(-Gamma) and the Extended Kalman filters: their capabilities and limitations. Debiased consistent measurement conversion from polar to Cartesian that allows the use of optimal linear filters in practical problems (implemented in the E-2C upgrade; applicable to long-range AEW radars).

The Interacting Multiple Model (IMM) estimation algorithm - a real-time implementable, self-adjusting variable-bandwidth, tracking filter.

Tracking in Clutter: The Probabilistic Data Association filter (PDAF).

Agile Beam Radar Allocation and ECM: The NSWC Benchmark Problem II for high-g targets in the presence of RGPO and jamming. Radar management (detection threshold, waveform, and revisit time selection, target RCS and jammer power estimation) and tracking with the IMMPDAF. Comparison with the MHT (Multiple Hypothesis Tracker). The real-time experiment with an Aegis SPY-1 and F-14s at Wallops.

Air Traffic Control Tracking: IMM vs. KF on real data (800 targets, from 5 FAA/JSS radars). How to evaluate estimation improvement without knowing the ground truth. Why multisensor tracking is cheaper computationally than single sensor tracking.

Large-Scale Tracking of Ground Targets: The Variable Structure IMM (VS-IMM) with topographic information and road constraints for precision tracking of ground targets with airborne GMTI radars. Application to a Joint STARS scenario. Evaluation of VSIMM vs. IMM and different depth assignment (optimization based MHT) algorithms. GEOP (Geometric enhancement of precision) from multiple (asynchronous) radar data fusion.

Acquisition of LO Targets: Track formation for low SNR targets. The CRLB in the presence of false measurements. The limit of extractable track information from cluttered data. Acquisition of a 4dB SNR TBM target with an ESA radar. The ML-PDA estimator applied to real EO data. Comparison with the MHT.

This Tutorial has a recommended book:

MULTITARGET-MULTISENSOR TRACKING: PRINCIPLES AND TECHNIQUES, 1995 Yaakov Bar-Shalom and Xiao-Rong Li Softcover. 8 1/2" x 11". Approx. 630 pages, 1001 equations, 250 figures, 200 references. ISBN 0-9648312-0-1.

You may order the book for 20% off = $96.00 (with free shipping) from Yaakov Bar-Shalom, 860-486-4823, or email ybs@ee.uconn.edu. Please order the book before April 15th, 2004 in order to receive it at your home before leaving for the conference (before April 23, 2004).


Dr. Yaakov BarShalom - Univ. of Conneticut

Yaakov BarShalom received the B.S. and M.S. degrees from the Technion, Israel Institute of Technology, in 1963 and 1967 and the Ph.D. degree from Princeton University in 1970, all in electrical engineering. Currently he is Board of Trustees Distinguished Professor in the Dept. of Electrical and Computer Engineering at the University of Connecticut. His current research interests are in estimation theory and target tracking and has published 7 books, over 300 papers and book chapters in these areas. He has been consulting to numerous companies and government agencies, and originated the series of MultitargetMultisensor Tracking short courses. He served as General Chairman of FUSION 2000 and President of ISIF in 2000 and 2002. He is corecipient of the M. Barry Carlton Award for the best paper in the IEEE Transactions on Aerospace and Electronic Systems in 1995 and 2001 and the 1998 University of Connecticut AAUP Excellence Award for Research. In 2002 he received the J. Mignona Data Fusion Award from the DoD JDL Data Fusion Group.

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