DocumentCode :
2072959
Title :
State estimation with quantized measurements in Wireless Sensor Networks
Author :
Xu Jian ; Li Jianxun
Author_Institution :
Dept. of Autom., Shanghai Jiao Tong Univ., Shanghai, China
fYear :
2010
fDate :
29-31 July 2010
Firstpage :
4857
Lastpage :
4862
Abstract :
The problem of state estimation with quantized measurements is considered. Due to the nonlinearity of the quantizer, estimating the system state is a nonlinear and non-Gaussian estimation problem even if the system is linear and Gaussian. A novel algorithm for approximate minimum mean square error (MMSE) state estimation with quantized measurement is proposed. The algorithm is based on careful analysis for the quantized measurement. Through effective information extraction from the quantitative measurement, the true measurement value is reestablished approximatively. Performance evaluation and comparison of the proposed algorithm with the existing methods by simulation of a typical tracking scenario in Wireless Sensor Networks(WSN) systems are presented. The numerical results show that the tracking algorithm is effective.
Keywords :
least mean squares methods; state estimation; wireless sensor networks; information extraction; minimum mean square error state estimation; nonGaussian estimation problem; nonlinear estimation problem; quantized measurements; tracking algorithm; wireless sensor networks; Approximation algorithms; Kalman filters; Noise; Quantization; State estimation; Wireless sensor networks; Decentralized State Estimation; Minimum Mean Squared Error (MMSE); Quantized Observations; Unscented Transform; Wireless Sensor Networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference (CCC), 2010 29th Chinese
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-6263-6
Type :
conf
Filename :
5572118
Link To Document :
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