期刊名称：International Journal of Soft Computing & Engineering
电子版ISSN：2231-2307
出版年度：2013
卷号：2
期号：6
页码：46-48
出版社：International Journal of Soft Computing & Engineering
摘要：Wireless sensor networks (WSN) have attracted significant attention recently. The distributed estimation problem is an important research topic in WSNs. In the distributed estimation problem, the fusion center estimates an unknown parameter based on information gathered from sensors. Usually, it is assumed that sensors have identical gains. However, this may not be true due to manufacture errors or environmental influence. In this paper, we assume sensor gains follow normal distribution and present a maximum likelihood estimation (MLE) approach for distributed estimation in WSNs with normally distributed sensor gains. Moreover, the Cramer-Rao lower bound (CRLB) corresponding to this MLE approach is also derived. Simulation results showed that the root square mean (RMS) estimation errors given by this MLE approach were close to the CRLB if the variance of the sensor gains is small. If the variance of the sensor gains was large, the RMS estimation errors were not close to the CRLB.
关键词：Distributed estimation; maximum likelihood;estimation; Gaussian distribution; wireless sensor networks.
