| In this paper, the spatial-temporal-frequency diversity to improve the detection performance of Radar Sensor Networks (RSN) in the presence of certain types of interference (clutter, jamming,
noise and interference between radar sensors) is studied. In order to reduce the interference between radar sensors and maximize the signal-to-interference-plus-noise ratio (SINR), we propose a method using the orthogonality criterion to design waveforms for radar sensors in the network. Besides the interference between radar sensors, performance of the network depends largely on other interference, especially clutter, which is extended in both angle
and range, and is spread in Doppler frequency. By using the spatial-temporal diversity, we can suppress effects of these interference. In this paper, we also propose a receiver for diversity combining in RSN. As an application example, we apply the spatial-temporal-frequency diversity scheme to improve the detection
performance or reduce the miss-detection probability at a low false alarm probability. Simulation results for both non-fluctuating targets and fluctuating targets show that the performance of our proposed scheme is superior to that of the single radar with the spatial-temporal diversity only. |
| Hung D. Ly received B.S. degree in Electrical Engineering from Posts and Telecommunications Institute of Technology, Vietnam, in 2002. Currently, he is pursuing M.S. degree in Electrical Engineering at The University of Texas at Arlington. His interests include Sensor Networks and Wireless Communications.
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. 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.
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