A novel particle filter for multiple target tracking with track-before-detect measurement models is proposed. Particle filters efficiently perform target tracking under nonlinear or non-Gaussian models. However, their application to multiple target tracking suffers from the curse of dimensionality. We introduce an efficient particle filter for multiple target tracking which deals with the curse of dimensionality better than previously developed methods. The proposed algorithm is tested and compared to other multiple target tracking particle filters.


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    Title :

    Adaptive Auxiliary Particle Filter for Track-Before-Detect With Multiple Targets


    Contributors:


    Publication date :

    2017-10-01


    Size :

    689907 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English