We consider the problem of Bayesian tracking of radar cross section. The adopted observation model employs the gamma family, which covers all Swerling cases in a unified framework. State dynamics are modeled using a nonstationary autoregressive gamma process. The principal component of the proposed solution is a nontrivial gamma approximation, applied during the time update recursion. The superior performance of the proposed approach is confirmed using simulations and a real-world dataset.


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    Titel :

    On Bayesian Tracking and Prediction of Radar Cross Section


    Beteiligte:
    Meller, Michal (Autor:in)


    Erscheinungsdatum :

    01.08.2019


    Format / Umfang :

    1142957 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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