UP	Paper 186	US-M-W	AT BOTTOM
Collaborative Signal Processing Using Radar Sensor Networks
Liang,Qilian		University of Texas at Arlington
In this paper, we propose a collaborative signal processing framework using waveform diversity in radar sensor networks (RSN). We study waveform diversity using constant frequency (CF) pulse waveform and linear frequency modulation (LFM) waveform, and compare their performance in automatic target recognition (ATR) with delay-doppler uncertainty. Simulation results show that CF pulse waveform and LFM waveform can achieve very similar performance in ATR with delay-doppler uncertainty using radar sensor networks. The ATR performance can tremendously be improved with larger number of radars in RSN.
Qilian Liang received the B.S. degree from Wuhan University, China, in 1993, M.S. degree from Beijing University of Posts and Telecommunications in 1996, and Ph.D degree from University of Southern California (USC) in May 2000, all in Electrical Engineering. 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 90 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.