Optimal sequential and distributed fusion for state estimation in cross-correlated noise

被引:107
作者
Yan, Liping [1 ]
Li, X. Rong [2 ]
Xia, Yuanqing [1 ]
Fu, Mengyin [1 ]
机构
[1] Beijing Inst Technol, Sch Automat, Key Lab Intelligent Control & Decis Complex Syst, Beijing 100081, Peoples R China
[2] Univ New Orleans, Dept Elect Engn, New Orleans, LA 70148 USA
关键词
State estimation; Cross-correlated noise; Sequential fusion; Distributed fusion; OPTIMAL LINEAR-ESTIMATION;
D O I
10.1016/j.automatica.2013.09.013
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 is concerned with the optimal state estimation for linear systems when the noises of different sensors are cross-correlated and also coupled with the system noise of the previous step. We derive the optimal linear estimation in a sequential form and for distributed fusion. They are both compared with the optimal batch fusion, suboptimal batch fusion, suboptimal sequential fusion, and the suboptimal distributed fusion where the cross-correlation between the noises are neglected. The comparison is in terms of theoretical filter mean square error and the real root mean square error. Simulation on a target tracking example is given to show the effectiveness of the presented algorithms. (C) 2013 Elsevier Ltd. All rights reserved.
引用
收藏
页码:3607 / 3612
页数:6
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