A new method of partially adaptive constant false-alarm rate (CFAR) detection is introduced. The processor implements a novel sequence of orthogonal subspace projections to decompose the Wiener solution in terms of the cross-correlation observed at each stage. The performance is evaluated using the general framework of space-time adaptive processing (STAP) for the cases of both known and unknown covariance. It is demonstrated that this new approach to partially adaptive STAP outperforms the more complex eigen-analysis approaches using both simulated DARPA Mountain Top data and true pulse-Doppler radar data collected by the MCARM radar.


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    Titel :

    Multistage partially adaptive STAP CFAR detection algorithm


    Beteiligte:
    Goldstein, J.S. (Autor:in) / Reed, I.S. (Autor:in) / Zulch, P.A. (Autor:in)


    Erscheinungsdatum :

    01.04.1999


    Format / Umfang :

    2447360 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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