| In radar sensor networks (RSN), radar members are likely to interfere with each other if their waveforms are not properly designed. In this paper, we propose an orthogonal waveform model for RSN, which eliminates interference when no doppler shift is
introduced. Additionally, we design both coherent and noncoherent RSN detection systems applying equal gain combination technique performed by clusterhead to take the advantage of spatial diversity. The latter scenario is more challenging as doppler-shift uncertainty results in more complicated implementation. Also, we analyzed the performance of both systems under the environment of doppler shift
and interference. Monte Carlo simulation illustrates that our technique provides much better detection performance than that of single radar for fluctuating targets, in terms of probability of false alarm and miss detection. Conclusions are drawn based on our
analysis and further related research areas are discussed. |
| Jing Liang received her BS and MS degree in Electrical Engineering from Beijing University of Posts and Telecommunications, China, in 2003 and 2006 respectively. She is now a Ph.D student at the University of Texas at Arlington. Her research interests include radar sensor networks, wireless communications, wireless networks and fuzzy logic system.
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 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.
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