Distributed Estimation and Detection in Wireless Sensor Networks
Zhenxing Luo

Zhenxing Luo, 721 Eastgate Ave, Apt. 2S, St. Louis.
Manuscript received on February 12, 2013. | Revised Manuscript Received on February 17, 2013. | Manuscript published on February 20, 2013. | PP: 13-16 | Volume-1 Issue-3, February 2013.
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Distributed estimation and detection are the two most important tasks of wireless sensor networks (WSNs). In the detection task, the fusion center needs to make a decision about the presence of a target. Usually, to make this decision, the fusion center uses a threshold. If the received signal is greater than the threshold, the fusion center considers the target is present. If the received signal is less than the threshold, the fusion center considers the target is absent. In the estimation problem, the fusion center will use a maximum likelihood estimation (MLE) method to estimate target location. In this MLE method, a threshold is needed for sensors to quantize information before sending information to the fusion center. This paper will investigate whether the two thresholds are identical. This problem is practically important because if the two thresholds are identical, the design of WSNs can be simplified.
Keywords: Distributed detection, distributed estimation, K-L distance, wireless sensor networks.