We develop a constant false-alarm rate (CFAR) approach for detecting a random N-dimensional complex vector in the presence of clutter or interference modeled as a zero mean complex Gaussian vector whose correlation properties are not known to the receiver. It is assumed that estimates of the correlation properties of the clutter/interference may be obtained independently by processing the received vectors from a set of reference cells. We characterize the detection performance of this algorithm when the signal to be detected is modeled as a zero-mean complex Gaussian random vector with unknown correlation matrix. Results show that for a prescribed false alarm probability and a given signal-to-clutter ratio (to be defined in the text), the detectability of Gaussian random signals depends on the eigenvalues of the matrix R/sub c//sup -1/R/sub s/. The nonsingular matrix R/sub c/ and the matrix R/sub s/ are the correlation matrices of clutter-plus-noise and signal vectors respectively. It is shown that the "effective" fluctuation statistics of the signal to be detected is determined completely by the eigenvalues of the matrix R/sub c//sup -1/R/sub s/. For example the signal to be detected has an effective Swerling II fluctuation statistics when all eigenvalues of the above matrix are equal. Swerling I fluctuation statistics results effectively when all eigenvalues except one are equal to zero. Eigenvalue distributions between these two limiting cases correspond to fluctuation statistics that lie between Swerling I and II models.<>


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    Titel :

    CFAR detection in clutter with unknown correlation properties


    Beteiligte:
    Raghavan, R.S. (Autor:in) / Qiu, H.F. (Autor:in) / McLaughlin, D.J. (Autor:in)


    Erscheinungsdatum :

    1995-04-01


    Format / Umfang :

    817669 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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