Distributed filtering for a class of discrete-time systems over wireless sensor networks

被引：28

作者：

Wen, Tao ^{[1
]}

Wen, Chuanbo ^{[2
]}

Roberts, Clive ^{[3
]}

Cai, Baigen ^{[1
]}

机构：

[1] Beijing Jiaotong Univ, Sch Elect & Informat Engn, Beijing 100044, Peoples R China

[2] Shanghai Dianji Univ, Coll Elect Engn, Shanghai 201306, Peoples R China

[3] Univ Birmingham, Birmingham Ctr Railway Res & Educ, Birmingham B15 2TT, W Midlands, England

来源：

JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS | 2020年 / 357卷 / 05期

基金：

中国国家自然科学基金;

关键词：

FUSION ESTIMATION;

D O I：

10.1016/j.jfranklin.2020.02.005

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper addresses the distributed filter design problem for a class of dynamic systems over wireless sensor networks. The missing measurements and the correlation among state noises and measurement noises are considered, where a set of mutually uncorrelated random variables is employed to describe the missing phenomena. Firstly, the construction of the designed filter is proposed and the prediction of the state at each node is given. Then, the filtering error covariance is presented and the filter parameters are determined to minimize the trace of such a covariance, where the network topology data are used to simplified the singular matrix. Subsequently, the relationship between the filter performance and missing probability of the measurement is discussed. Finally, a numerical simulation is presented to illustrate the effectiveness and capability of the proposed distributed filters. (c) 2020 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

引用

页码：3038 / 3055

页数：18

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