In practical tracking applications, the target detection performance may be unknown and also change rapidly in time. This work considers a network of sensors and develops a target-tracking procedure able to adapt and react to the time-varying changes of the network detection probability. The proposed adaptive tracker is validated using extensive computer simulations and real-world experiments, testing a network of high-frequency radars for maritime surveillance and an underwater network of autonomous underwater vehicles for antisubmarine warfare.


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    Titel :

    Multisensor adaptive bayesian tracking under time-varying target detection probability


    Beteiligte:
    Papa, Guiseppe (Autor:in) / Braca, Paolo (Autor:in) / Horn, Steven (Autor:in) / Marano, Stefano (Autor:in) / Matta, Vincenzo (Autor:in) / Willett, Peter (Autor:in)


    Erscheinungsdatum :

    2016-10-01


    Format / Umfang :

    1984798 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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