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.
Subspace selection for partially adaptive sensor array processing
IEEE Transactions on Aerospace and Electronic Systems ; 33 , 2 ; 539-544
01.04.1997
1769753 byte
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Subspace Selection for Partially Adaptive Sensor Array Processing
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