Distributed fusion estimation for multi-sensor asynchronous sampling systems with correlated noises

ABSTRACT

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.

KEYWORDS:

• Multi-sensor system
• asynchronous sampling
• correlated noise
• cross-covariance matrix
• distributed fusion filter

Acknowledgments

The authors would like to express their sincere thanks to the editor and the reviewers for their helpful assessments and comments.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [grant number 61174139], [grant number 61573132]; Heilongjiang Province Outstanding Youth fund [grant number JC201412]: Chang Jiang Scholar Candidates Program for Provincial Universities in Heilongjiang [grant number 2013CJHB005]; Program for Graduate Innovation Scientific Research of Heilongjiang University [grant number YJSCX2015-001HLJU].

Notes on contributors

Honglei Lin

Honglei Lin was born in Heilongjiang, China in 1986. She received the B.S. degree in department of mathematics from Mudanjiang Normal University, China, in 2010 and M.E. degree in School of Mathematics science from Heilongjiang University, China, in 2013, respectively. Currently, she is working for her Ph.D. degree in Heilongjiang University. Her main research interests are state estimation and information fusion filtering.

Shuli Sun

Shuli Sun was born in Heilongjiang, China in 1971. He received the B.S. degree in department of mathematics and M.E. degree in department of automation from Heilongjiang University, China, in 1996 and 1999, respectively. He received the Ph.D. degree in School of Astronautics from Harbin Institute of Technology, China, in 2004. He is a Research Fellow in Nanyang Technological University, Singapore, from 2006 to 2007. Since 2006, he has been a Professor in the School of Electronic Engineering of Heilongjiang University, China. His research interests are in the areas of state estimation, signal processing, information fusion and sensor network.