In this paper we present an approximate multi-Bernoulli filter and an approximate hybrid multi-Bernoulli cardinalized probability hypothesis density filter for superpositional sensors. The approximate-filter equations are derived by assuming that the predicted and posterior multitarget states have the same form and propagating the probability hypothesis density function for each independent component of the multitarget state. We examine the performance of the filters in a simulated acoustic sensor network and a radio frequency tomography application.


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    Title :

    Hybrid multi-Bernoulli and CPHD filters for superpositional sensors


    Contributors:


    Publication date :

    2015-10-01


    Size :

    764716 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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