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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    Titel :

    Data association for multiple target tracking using Hopfield neural network


    Beteiligte:
    Leung, H. (Autor:in) / Blanchette, M. (Autor:in)


    Erscheinungsdatum :

    01.01.1994


    Format / Umfang :

    244867 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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