UP	Paper 122	US-T-I	AT BOTTOM
Radar Sensor Networks for Automatic Target Recognition with Delay-Doppler Uncertainty
Liang,Qilian		University of Texas at Arlington
Automatic target recognition (ATR) in target search phase is very challenging because the target range and mobility are not yet perfectly known, which results in delay-doppler uncertainty. In this paper, we firstly perform some theoretical studies on radar sensor network (RSN) design based linear frequency modulation (LFM) waveform: (1) the conditions for waveform co-existence, (2) interferences among waveforms in RSN, (3) waveform diversity in RSN. Then we apply RSN to ATR with delay-doppler uncertainty and propose maximum-likekihood (ML) ATR algorithms for fluctuating target and nonfluctuating target. Simulation results show that our RSN vastly reduces the ATR error comparing to a single radar system in ATR with delay-doppler uncertainty.
Qilian Liang received the Ph.D degree in Electrical Engineering from University of Southern California (USC) in May 2000. Dr. Liang joined the faculty of the University of Texas at Arlington in August 2002. Prior to that he was a Member of Technical Staff in Hughes Network Systems Inc at San Diego, California. His research interests include Sensor networks (energy efficiency, cross layer design, optimal sensor deployment, etc), wireless communications, wireless networks, communication system and communication theory, signal processing for communications, fuzzy logic systems and applications, multimedia network traffic modeling and classification, collaborative and distributed signal processing. Dr. Liang has published more than 100 journal and conference papers, 4 book chapters, and has 6 U.S. patents pending. He received 2002 IEEE Transactions on Fuzzy Systems Outstanding Paper Award, 2003 U.S. Office of Naval Research (ONR) Young Investigator Award, and 2005 UTA College of Engineering Outstanding Young Faculty Award.