文献类型：期刊文献

英文题名：Deterministic Sensor Selection for Centralized State Estimation Under Limited Communication Resource

作者：Yang, Chao[1];Wu, Junfeng[2];Ren, Xiaoqiang[3];Yang, Wen[1];Shi, Hongbo[1];Shi, Ling[3]

机构：[1]E China Univ Sci & Technol, Dept Automat, Key Lab Adv Control & Optimizat Chem Proc, Shanghai 200237, Peoples R China;[2]Royal Inst Technol, Sch Elect Engn, Stockholm, Sweden;[3]Hong Kong Univ Sci & Technol, Dept Elect & Comp Engn, Kowloon, Hong Kong, Peoples R China

年份：2015

卷号：63

期号：9

起止页码：2336

外文期刊名：IEEE TRANSACTIONS ON SIGNAL PROCESSING

收录：;EI(收录号：20151600757859);WOS:【SCI-EXPANDED(收录号:WOS:000352283900013)】；

基金：The work by X. Ren and L. Shi is supported by an grant HK RGC GRF 618612. The work by W. Yang is supported by NSFC under grant no. 61203158 and the Innovation Program of Shanghai Municipal Education Commission.

语种：英文

外文关键词：Networked state estimation; sensor scheduling; sensor selection; convex optimization; modified algebraic Riccati equation (MARE)

摘要：This paper studies a sensor selection problem. A group of sensors measure the state of a process and send their measurements to a remote estimator. Due to communication constraints, only limited sensors are allowed to communicate with the estimator. The paper intends to answer which sensors should be chosen such that the estimation performance of the estimator is optimized. Both reliable and packet-dropping channels are considered. It is required to minimize the steady-state estimation error covariance for reliable channels and to minimize the upper bound of the expected estimation error covariance for packet-dropping channels. For both scenarios, the original optimization problems are transformed to problems which can be solved by convex optimization techniques.