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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    Title :

    Multisensor adaptive bayesian tracking under time-varying target detection probability


    Contributors:


    Publication date :

    2016-10-01


    Size :

    1984798 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English