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Distributed Robust Kalman Filtering with Unknown and Noisy Parameters in Sensor Networks
Joint Authors
Liu, Cheng-Lin
Chen, Donghua
Zhang, Ya
Chen, Yangyang
Source
Discrete Dynamics in Nature and Society
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-12-02
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
This paper investigates the distributed filtering for discrete-time-invariant systems in sensor networks where each sensor’s measuring system may not be observable, and each sensor can just obtain partial system parameters with unknown coefficients which are modeled by Gaussian white noises.
A fully distributed robust Kalman filtering algorithm consisting of two parts is proposed.
One is a consensus Kalman filter to estimate the system parameters.
It is proved that the mean square estimation errors for the system parameters converge to zero if and only if, for any one system parameter, its accessible node subset is globally reachable.
The other is a consensus robust Kalman filter to estimate the system state based on the system matrix estimations and covariances.
It is proved that the mean square estimation error of each sensor is upper-bounded by the trace of its covariance.
An explicit sufficient stability condition of the algorithm is further provided.
A numerical simulation is given to illustrate the results.
American Psychological Association (APA)
Chen, Donghua& Zhang, Ya& Liu, Cheng-Lin& Chen, Yangyang. 2018. Distributed Robust Kalman Filtering with Unknown and Noisy Parameters in Sensor Networks. Discrete Dynamics in Nature and Society،Vol. 2018, no. 2018, pp.1-11.
https://search.emarefa.net/detail/BIM-1152823
Modern Language Association (MLA)
Chen, Donghua…[et al.]. Distributed Robust Kalman Filtering with Unknown and Noisy Parameters in Sensor Networks. Discrete Dynamics in Nature and Society No. 2018 (2018), pp.1-11.
https://search.emarefa.net/detail/BIM-1152823
American Medical Association (AMA)
Chen, Donghua& Zhang, Ya& Liu, Cheng-Lin& Chen, Yangyang. Distributed Robust Kalman Filtering with Unknown and Noisy Parameters in Sensor Networks. Discrete Dynamics in Nature and Society. 2018. Vol. 2018, no. 2018, pp.1-11.
https://search.emarefa.net/detail/BIM-1152823
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1152823