期刊
AUTOMATICA
卷 49, 期 12, 页码 3607-3612出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.automatica.2013.09.013
关键词
State estimation; Cross-correlated noise; Sequential fusion; Distributed fusion
资金
- NSFC [61004139, 61004059, 91120003, 61225015, 61220001]
- BNSF [4132042]
- outstanding youth foundation of BIT
- NASA/LEQSF [NNX13AD29A]
- Program 973 [2013CB329405]
- ONR-DEPSCoR [N00014-09-1-1169]
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.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据