This paper introduces a cross-spectral metric for subspace selection and rank reduction in partially adaptive minimum variance array processing. The counter-intuitive result that it is suboptimal to perform rank reduction via the selection of the subspace formed by the principal eigenvectors of the array covariance matrix is demonstrated. A cross-spectral metric is shown to be the optimal criterion for reduced-rank Wiener filtering.


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    Titel :

    Subspace selection for partially adaptive sensor array processing


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


    Erscheinungsdatum :

    01.04.1997


    Format / Umfang :

    1769753 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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