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Subspace selection for partially adaptive sensor array processing

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2 Author(s)
Goldstein, J.Scott ; Dept. of Electr. Eng., Univ. of Southern California, Los Angeles, CA, USA ; Reed, Irving S.

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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Aerospace and Electronic Systems, IEEE Transactions on  (Volume:33 ,  Issue: 2 )