Abstract
This paper studies the sensor selection problem for random field estimation in wireless sensor networks. The authors first prove that selecting a set of l sensors that minimize the estimation error under the D-optimal criterion is NP-complete. The authors propose an iterative algorithm to pursue a suboptimal solution. Furthermore, in order to improve the bandwidth and energy efficiency of the wireless sensor networks, the authors propose a best linear unbiased estimator for a Gaussian random field with quantized measurements and study the corresponding sensor selection problem. In the case of unknown covariance matrix, the authors propose an estimator for the covariance matrix using measurements and also analyze the sensitivity of this estimator. Simulation results show the good performance of the proposed algorithms.
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This work was supported by the National Natural Science Foundation of China-Key Program under Grant No. 61032001 and the National Natural Science Foundation of China under Grant No. 60828006. Part of this work was presented at the 29th China Control Conference, Beijing, China, July 2010.
This paper was recommended for publication by Editor Yiguang HONG.
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Weng, Y., Xie, L. & Xiao, W. Sensor selection for random field estimation in wireless sensor networks. J Syst Sci Complex 25, 46–59 (2012). https://doi.org/10.1007/s11424-012-0105-6
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DOI: https://doi.org/10.1007/s11424-012-0105-6