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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    Title :

    On Bayesian Tracking and Prediction of Radar Cross Section


    Contributors:


    Publication date :

    2019-08-01


    Size :

    1142957 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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