期刊
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
卷 48, 期 5, 页码 952-960出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/00207721.2016.1224953
关键词
Multi-sensor system; asynchronous sampling; correlated noise; cross-covariance matrix; distributed fusion filter
类别
资金
- National Natural Science Foundation of China [61174139, 61573132]
- Heilongjiang Province Outstanding Youth fund [JC201412]
- Chang Jiang Scholar Candidates Program for Provincial Universities in Heilongjiang [2013CJHB005]
- Program for Graduate Innovation Scientific Research of Heilongjiang University [YJSCX2015-001HLJU]
This paper is concerned with the distributed fusion estimation problem for a class of multi-sensor asynchronous sampling systems with correlated noises. The state updates uniformly and the sensors sample randomly. Based on the measurement augmentation method, the asynchronous sampling system is transformed to the synchronous sampling one. Local filter is designed by using an innovation analysis approach. Then, the filtering error cross-covariance matrix between any two local filters is derived. Finally, the optimal distributed fusion filter is proposed by using matrix-weighted fusion algorithm in the linear minimum variance sense. Simulation results show the effectiveness of the proposed algorithms.
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