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.


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    Titel :

    Distributed Estimation for Markov Jump Systems via Diffusion Strategies


    Beteiligte:
    Wenling Li, (Autor:in) / Yingmin Jia, (Autor:in)


    Erscheinungsdatum :

    2017-02-01


    Format / Umfang :

    810583 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch