The probabilistic data association (PDA) algorithm for tracking in clutter contains a stochastic (data-dependent) Riccati equation for updating the estimation error covariance matrix. This note details a simple analytic approximation to the stochastic Riccati equation that allows precomputation of the estimation error covariance matrices. The potential of the approximation for performance analysis of PDA-based tracking algorithm is demonstrated using a simple example.


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    Title :

    A contribution to performance prediction for probabilistic data association tracking filters


    Contributors:
    Kershaw, D.J. (author) / Evans, R.J. (author)


    Publication date :

    1996-07-01


    Size :

    1506859 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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