The focus of this article is to tackle the challenging task of unresolved-group object (UO) tracking by exploiting the Poisson multi-Bernoulli mixture (PMBM) filter, named UO-PMBM. Specifically, according to the UO likelihood function, the probability generating functional tool and functional derivative are first used to derive the filtering recursion expressions of the UO-PMBM. Then, detailed descriptions of the Gaussian mixture (GM) implementations are described. Lastly, the effectiveness of the proposed UO-PMBM approach is demonstrated through simulation experiments.


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    Titel :

    PMBM-Based Unresolved-Group Object Tracking


    Beteiligte:
    Li, Guchong (Autor:in) / Li, Gang (Autor:in) / He, You (Autor:in)


    Erscheinungsdatum :

    01.08.2024


    Format / Umfang :

    1359699 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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