In this letter, we have developed a neural network (NN) based upon modeling fields for improved object tracking. Models for ground moving target indicator (GMTI) tracks have been developed as well as neural architecture incorporating these models. The neural tracker overcomes combinatorial complexity of tracking in highly cluttered scenarios and results in about 20-dB (two orders of magnitude) improvement in signal-to-clutter ratio.


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    Titel :

    Neural networks for improved tracking


    Beteiligte:
    Perlovsky, L.I. (Autor:in) / Deming, R.W. (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    2007


    Format / Umfang :

    4 Seiten, 12 Quellen




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Print


    Sprache :

    Englisch




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