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• W3136131021 abstract "This article is concerned with a distributed filtering problem for Markov jump systems subject to the measurement loss with unknown probabilities. A centralized robust Kalman filter is designed by using variational Bayesian methods and a modified interacting multiple model method based on information theory (IT-IMM). Then, a distributed robust Kalman filter based on the centralized filter and a hybrid consensus method called hybrid consensus on measurement and information (HCMCI) is designed. Moreover, boundedness of the estimation errors and the estimation error covariances are studied for the distributed robust Kalman filter." @default.
• W3136131021 created "2021-03-29" @default.
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• W3136131021 date "2022-10-01" @default.
• W3136131021 modified "2023-10-14" @default.
• W3136131021 title "Distributed Robust Kalman Filtering for Markov Jump Systems With Measurement Loss of Unknown Probabilities" @default.
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• W3136131021 doi "https://doi.org/10.1109/tcyb.2021.3062641" @default.
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