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.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Multistage partially adaptive STAP CFAR detection algorithm


    Contributors:
    Goldstein, J.S. (author) / Reed, I.S. (author) / Zulch, P.A. (author)


    Publication date :

    1999-04-01


    Size :

    2447360 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    CFAR detection and estimation for STAP radar

    Reed, I.S. / Gau, Y.L. / Truong, T.K. | IEEE | 1998


    CFAR Detection and Estimation for STAP Radar

    Reed, I.S. | Online Contents | 1998


    Partially Adaptive STAP using the FRACTA Algorithm

    Shackelford, A.K. | Online Contents | 2009


    Partially Adaptive STAP using the FRACTA Algorithm

    Shackelford, A.K. / Gerlach, K. / Blunt, S.D. | IEEE | 2009