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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Session 4B.1
Application of Reduced State Estimation to Multisensor Fusion with Out-of-Sequence Measurements

Purusottam Mookerjee - Lockheed Martin Maritime Systems & Sensors, Frank Reifler - Lockheed Martin Maritime Systems & Sensors

Tue, 27 April 2004, 4:10 PM - 5:30 PM


Abstract

In this paper a filtering application of processing multisensor measurements with delays is considered. Because of delays, measurements fed by geographically dispersed sensors to a processing site may arrive out of time sequence. Unlike smoothing or filtering, optimal processing of an out-of-sequence measurement is not a standard problem in filtering theory for which a definitive approach has yet been developed. An optimal reduced state estimator, derived in previous work, is applied to this problem. A simulation example of multisensor fusion is presented, in which one sensor feeds highly accurate but delayed measurements to be fused with a second sensor?s less accurate measurements having no delay. We demonstrate uniform improvement in performance using this algorithm over two traditional approaches.

Bios

Dr. Purusottam Mookerjee - Lockheed Martin Maritime Systems & Sensors

Purusottam Mookerjee received the B. Tech. Degree from the Indian Institute of Technology, Kharagpur, India and the M.S. and Ph.D. degrees from the University of Connecticut, Storrs, Connecticut. He has held positions in both industry and academia in his professional career. Currently, he is a Principal Member of the Engineering Staff of Lockheed Martin Corporation Maritime Systems and Sensors, Moorestown, NJ. He is also a Part Time Lecturer in Rutgers, The State University of New Jersey. His interests are in advanced topics on estimation and control theory, mathematical modeling, and voice and data networks.

Dr. Frank Reifler - Lockheed Martin Maritime Systems & Sensors

Frank Reifler received his Ph.D. degree from the University of Washington at Seattle, Washington in mathematics. He has held positions in both academia and industry. Currently, he is a Principal Member of the Engineering Staff of Lockheed Martin Corporation Maritime Systems and Sensors, Moorestown, NJ. His interests are in signal processing, optimal decision, estimation and control theory, and mathematical and theoretical physics.

 
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