We consider the problem of distributed estimation for Markov jump systems. A distributed interacting multiple model Kalman filter is developed based on the diffusion strategy, where the local measurements, the mode-conditioned estimates, and the likelihoods are exchanged between neighboring nodes. The proposed filter leads to stable estimates for all nodes as long as at least one node is stable in a connected network. Simulation results show that the proposed approach outperforms the existing techniques.
Distributed Estimation for Markov Jump Systems via Diffusion Strategies
IEEE Transactions on Aerospace and Electronic Systems ; 53 , 1 ; 448-460
2017-02-01
810583 byte
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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