In a surveillance situation the origin of each measurement is uncertain. Each measurement may be a false (clutter) measurement, or it may be a target detection. Probabilistic methods are usually used to discriminate between the clutter and the target measurements. Clutter measurement density is an important parameter in this process. The values of the clutter measurement density in the surveillance space are rarely known a priori, and are usually estimated using sensor data and track information. A novel approach is presented and evaluated for estimating the values of clutter measurement density, which significantly enhances target tracking. Simulation results validate this approach.


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    Titel :

    Adaptive Clutter Measurement Density Estimation for Improved Target Tracking


    Beteiligte:
    Taek Lyul Song, (Autor:in) / Musicki, D (Autor:in)


    Erscheinungsdatum :

    01.04.2011


    Format / Umfang :

    797428 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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