DocumentCode :
1720379
Title :
Observability of linear systems for Kalman filtering with packet losses
Author :
You Keyou ; Song Shiji
Author_Institution :
Dept. of Autom., Tsinghua Univ., Beijing, China
fYear :
2013
Firstpage :
4725
Lastpage :
4730
Abstract :
This paper provides a short survey of the state-of-the-art results on the mean square stability of Kalman filtering with packet losses, and discusses several approaches to study the stability of the estimation error covariance matrix of the intermittent Kalman filter. In comparison with the Riccati approach by Sinopoli et al, the observability approach is more suitable to exactly characterize the effect of random packet losses on the stability of the estimation error covariance matrix. Moreover, it is shown that this approach can be used to design the coding or sampling strategies to reduce the effect of packet losses on the stability of the intermittent Kalman filter.
Keywords :
Kalman filters; Riccati equations; covariance matrices; mean square error methods; observability; Kalman filtering; Riccati approach; coding strategy; estimation error covariance matrix; intermittent Kalman filter; linear systems; mean square stability; observability; packet losses; sampling strategy; Encoding; Kalman filters; Observability; Packet loss; Stability analysis; Vectors; Kalman filtering; Linear systems; Riccati; observability; packet losses;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference (CCC), 2013 32nd Chinese
Conference_Location :
Xi´an
Type :
conf
Filename :
6640255
Link To Document :
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