Title
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.
Year
DOI
Venue
2017
10.1080/00207721.2016.1224953
Int. J. Systems Science
Keywords
Field
DocType
Multi-sensor system, asynchronous sampling, correlated noise, cross-covariance matrix, distributed fusion filter
Minimum-variance unbiased estimator,Computer science,Matrix (mathematics),Control theory,Fusion,Filter (signal processing),Asynchronous sampling,Sampling (statistics)
Journal
Volume
Issue
ISSN
48
5
0020-7721
Citations 
PageRank 
References 
6
0.43
13
Authors
2
Name
Order
Citations
PageRank
Honglei Lin1679.27
Shuli Sun273452.41