Data association consists of assigning measurements to the predicted track positions in the multiple target tracking application. The data association problem can be structured in a basic framework very similar to that of the classic travelling salesman problem (TSP). The derivation of the energy function is presented, and the solution is based on a modified Hopfield network which uses the Runge-Kutta method and Aiyer (1990) network's structure. We demonstrate the feasibility of applying neural network technology to multitarget tracking using simulated and real-life radar data. The modified Hopfield tracker is also observed to have better performance than the original Hopfield network.<>


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    Title :

    Data association for multiple target tracking using Hopfield neural network


    Contributors:
    Leung, H. (author) / Blanchette, M. (author)


    Publication date :

    1994-01-01


    Size :

    244867 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Data Association for Multiple Target Tracking using Hopfield Neural Network

    Leung, H. / Blanchette, M. / IEEE; Hong Kong Chapter of Signal Processing | British Library Conference Proceedings | 1994


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