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- W338072922 abstract "Abstract : Adaptive methods of beamforming that yield high resolution beam outputs require a much greater numerical intensity than conventional Fourier techniques of beamforming. Reduction of the adaptive dimension of these data dependent beamformers can alleviate the numerical intensity problem with a negligible loss in performance. The adaptive dimension reduction may be accomplished by a matrix premultiplication of the array sensor data. The matrix premultiplication, known as matrix preprocessing, transforms the N dimension array data vector into an M dimensional space where M < N. The M dimensional data is then beamformed with a minimum variance distortionless response (MVDR) adaptive beamformer. Another method of reducing the adaptive dimension is by the approximation of the covariance or cross spectral density matrix (CSDM) by its dominant or strongest eigenvectors." @default.
- W338072922 created "2016-06-24" @default.
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- W338072922 date "1990-07-31" @default.
- W338072922 modified "2023-09-26" @default.
- W338072922 title "Reduced Dimension Adaptive Beamforming" @default.
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