We use the two-dimensional track-to-track assignment problem to analyze the trade-off between accuracy and runtime performance for three methods of estimating track-to-track assignment probabilities: enumeration of the k-best data association hypotheses, importance sampling (IS), and Markov chain Monte Carlo (MCMC) estimation. We also characterize the appropriate operating regime for each method.


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    Title :

    A Comparison of Methods for Estimating Track-to-Track Assignment Probabilities


    Contributors:
    Kragel, B. (author) / Herman, S. (author) / Roseveare, N. (author)


    Publication date :

    2012-07-01


    Size :

    3307933 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





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