Novel Student's t based approaches for formulating a filter and smoother, which utilize heavy tailed process and measurement noise models, are found through approximations of the associated posterior probability density functions. Simulation results for manoeuvring target tracking illustrate that the proposed methods substantially outperform existing methods in terms of the root mean square error.


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    Titel :

    Robust student’s t based nonlinear filter and smoother


    Beteiligte:
    Yulong Huang (Autor:in) / Yonggang Zhang (Autor:in) / Ning Li (Autor:in) / Chambers, Jonathon (Autor:in)


    Erscheinungsdatum :

    01.10.2016


    Format / Umfang :

    509437 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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