Title
Distributed filtering for discrete-time linear systems with fading measurements and time-correlated noise.
Abstract
This paper studies the problem of distributed filtering for discrete-time linear systems with fading measurements and time-correlated noise over a sensor network. To address the problem of the time-correlated measurement noise, the measurement differencing approach is adopted to define a new measurement such that the noise in the new measurement is not time-correlated any longer. Based on the new measurement, the innovation-based and the consensus-based distributed filters are proposed for each sensor by using its neighboring information. By resorting to the graph properties, the filter gain matrices are designed for each sensor to develop optimal distributed filters in the sense of minimum variance. Moreover, suboptimal distributed filters are proposed to reduce the computational cost and the communication cost. The performance of the distributed filters is analyzed with respect to the fading factor. Simulation results are provided to show the effectiveness of the proposed filters.
Year
DOI
Venue
2017
10.1016/j.dsp.2016.10.003
Digital Signal Processing
Keywords
Field
DocType
Distributed filtering,Kalman filter,Fading measurement,Time-correlated measurement noise
Distributed filtering,Minimum-variance unbiased estimator,Graph property,Linear system,Matrix (mathematics),Fading,Control theory,Computer science,Kalman filter,Wireless sensor network
Journal
Volume
ISSN
Citations 
60
1051-2004
11
PageRank 
References 
Authors
0.50
15
3
Name
Order
Citations
PageRank
Wenling Li122718.83
Yingmin Jia21743135.37
Junping Du378991.80