In this article, we consider the distributed nonlinear state estimation over sensor networks under the diffusion Kalman filter paradigm, where data only exchanges among the neighbourhoods of sensors. We first obtain a novel nonlinear Kalman filter with intermittent observations based on cubature Kalman filter. After that, its equivalent information filter is derived, and the proposed diffusion cubature Kalman filter with intermittent observations is designed based on this information filter. The effectiveness of proposed algorithms is demonstrated by a typical target tracking example, and our algorithm has similar estimation accuracy when comparing with existing algorithms while consuming less computation and communication resources.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Diffusion nonlinear Kalman filter with intermittent observations


    Contributors:
    Wang, Guoqing (author) / Li, Ning (author) / Zhang, Yonggang (author)


    Publication date :

    2018-12-01


    Size :

    9 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    Partial Diffusion Kalman Filter With Adaptive Combiners

    Khalili, Azam / Vahidpour, Vahid / Rastegarnia, Amir et al. | IEEE | 2021



    Nonlinear Filters: Beyond the Kalman Filter

    Daum, F. | Online Contents | 2005


    Kalman filter orbit improvement from Kootwijk laser range observations

    Wakker, K.F. / Ambrosius, B.A.C. / van Hulzen, J.J.P. | Elsevier | 1981


    Quaternion Estimation from Vector Observations Using a Matrix Kalman Filter

    Choukroun, Daniel / Weiss, Haim / Bar-Itzhack, Itzhack et al. | AIAA | 2005