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.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Distributed Estimation for Markov Jump Systems via Diffusion Strategies


    Contributors:
    Wenling Li, (author) / Yingmin Jia, (author)


    Publication date :

    2017-02-01


    Size :

    810583 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English