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Kalman Filtering Over Lossy Networks Under Switching Sensors
Author(s) -
You Keyou,
Sui Tianju,
Fu Minyue
Publication year - 2015
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.975
Subject(s) - lossy compression , kalman filter , estimator , independent and identically distributed random variables , control theory (sociology) , covariance , stability (learning theory) , wireless sensor network , computer science , network packet , packet loss , mathematics , algorithm , random variable , statistics , artificial intelligence , computer network , control (management) , machine learning
In this paper, we study the mean square stability of Kalman filtering of a discrete‐time stochastic system under two periodically switching sensors. The sensor measurements are sent to a remote estimator over a lossy channel whose packet loss process is independent and identically distributed. We prove that the problem can be converted into the stability analysis of Kalman filtering using two sensors at each time, and the measurements of each sensor are transmitted to the estimator via an independent lossy channel of the same packet loss rate. Some necessary and/or sufficient conditions for stability of the estimation error covariance matrices are derived. Moreover, the effect of the sensor switching on the filter stability is revealed. Their implications and relationships with related results in the literature are discussed.