Predetection fusion can be indispensable for multisensor/multitarget tracking using large networks of low quality sensors. Previously we derived both the "optimal" generalized likelihood ratio test (GLRT) and a more practicable contact-sifting variant. Unfortunately, the gaps between the two in terms both of computation time and performance are not inconsiderable. In this paper we propose an approach, based on random finite sets (RFS) and implemented by Markov chain Monte Carlo (MCMC) simulation, that offers a good balance between run time and metrics for the tracking results.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    RFS MCMC Predetection Fusion Applied to Multistatic Sonar Data


    Beteiligte:
    Georgescu, R. (Autor:in) / Willett, P. (Autor:in)


    Erscheinungsdatum :

    01.10.2012


    Format / Umfang :

    4376477 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Predetection fusion: resolution cell grid effects

    Rago, C. / Willett, P. / Alford, M. | IEEE | 1999


    Distributed tracking in multistatic sonar

    Coraluppi, S. / Carthel, C. | IEEE | 2005


    The Case for Like-Sensor Predetection Fusion

    Willett, P. | Online Contents | 1994



    The case for like-sensor predetection fusion

    Willett, P. / Alford, M. / Vannicola, V. | IEEE | 1994