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| Error Exponents for Target-Class Detection in a Sensor Network | |||
| Misra,Saswat | Army Research Laboratory | ||
| Tong,Lang | Cornell University | ||
| Ephremides,Tony | University of Maryland | ||
| We study the target class detection performance of a wireless sensor network with a structured node topology. The target is assumed to be in the far-field of the network and positioned at an angle $\theta$, which may be known or unknown. The target produces a random signal field that is spatially correlated and dependent on $\theta$ and the target's class $i$, $i \in \{0,1\}$. We study the Neyman-Pearson detection error exponent for this scenario using large deviations theory. When $\theta$ is known, we derive a closed-form analytic expression for the probability of miss error exponent and show that it is monotonically decreasing in the node spacing $d$ and bounded as $d \rightarrow 0$. When $\theta$ is unknown, we study its estimation using the Generalized Likelihood Ratio Test (GLRT). We study the error exponent of the GLRT using both analytic techniques and numerical simulations. | |||
| Saswat Misra was born in College Park, MD, USA, in 1978. He received the B.S. in electrical engineering from the University of Maryland at College Park in 2000 and the M.S. in electrical engineering from the University of Illinois at Urbana-Champaign in 2002. Since 2002, he has been a Research Scientist at ARL in Adelphi, MD in the Communications and Network Systems division. Since Fall 2005, he has been a Ph.D. candidate at Cornell University. Mr. Misra is currently studying routing and security issues in wireless networks. He previously worked on optimal training design for wireless communication systems; an area in which he has published several papers and holds two patents (pending). | |||