文献类型：期刊文献

英文题名：Stochastic sensor activation for distributed state estimation over a sensor network

作者：Yang, Wen[1];Chen, Guanrong[2];Wang, Xiaofan[3];Shi, Ling[4]

机构：[1]E China Univ Sci & Technol, Key Lab Adv Control & Optimizat Chem Proc, Minist Educ, Shanghai 200237, Peoples R China;[2]City Univ Hong Kong, Dept Elect Engn, Hong Kong, Hong Kong, Peoples R China;[3]Shanghai Jiao Tong Univ, Dept Automat, Shanghai 200240, Peoples R China;[4]Hong Kong Univ Sci & Technol, Dept Elect & Comp Engn, Hong Kong, Hong Kong, Peoples R China

年份：2014

卷号：50

期号：8

起止页码：2070

外文期刊名：AUTOMATICA

收录：;EI(收录号：20143218033428);WOS:【SCI-EXPANDED(收录号:WOS:000340696000010)】；

基金：This work by W. Yang is partially supported by NSFC under grant no. 61203158, the Innovation Program of Shanghai Municipal Education Commission under Grant No. 14zz55 and the Fundamental Research Funds for Central Universities under Grant No. WH1214014. This work by G.R. Chen is partially supported by an HK RGC GRF grant CityU1109/12. This work by X.F. Wang is partially supported by NSFC under grant no. 61374176. This work by L. Shi is partially supported by an HK RGC GRF grant 618612. The material in this paper was not presented at any conference. This paper was recommended for publication in revised form by Associate Editor Giancarlo Ferrari-Trecate under the direction of Editor Ian R. Petersen.

语种：英文

外文关键词：Distributed state estimation; Sensor scheduling; Consensus

摘要：We consider distributed state estimation over a resource-limited wireless sensor network. A stochastic sensor activation scheme is introduced to reduce the sensor energy consumption in communications, under which each sensor is activated with a certain probability. When the sensor is activated, it observes the target state and exchanges its estimate of the target state with its neighbors; otherwise, it only receives the estimates from its neighbors. An optimal estimator is designed for each sensor by minimizing its mean-squared estimation error. An upper and a lower bound of the limiting estimation error covariance are obtained. A method of selecting the consensus gain and a lower bound of the activating probability is also provided. (C) 2014 Elsevier Ltd. All rights reserved.