We present reduced-complexity nonlinear filtering algorithms for image-based tracking of maneuvering targets. In image-based target tracking, the mode of the target is observed as a Markov modulated Poisson process (MMPP) and the aim is to compute optimal estimates of the target's state. We present a reduced complexity algorithm in two steps. First, a gauge transformation is used to reexpress the filtering equations in a form that is computationally more efficient for time discretization than naive discretization of the filtering equations. Second, a spatial aggregation algorithm with guaranteed performance bounds is presented for the time-discretized filters. A numerical example illustrating the performance of the resulting reduced-complexity filtering algorithms for a switching turn-rate model is presented.


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    Title :

    Reduced spatio-temporal complexity MMPP and image-based tracking filters for maneuvering targets


    Contributors:
    Krishnamurthy, V. (author) / Dey, S. (author)


    Publication date :

    2003-10-01


    Size :

    744591 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





    Reduced Complexity Spatio-Temporal Image Based Tracking for Maneuvering Targets

    Krishnamurthy, V. / Dey, S. / International Society of Information Fusion et al. | British Library Conference Proceedings | 2002