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Please use this identifier to cite or link to this item: http://eprint.iitd.ac.in/handle/2074/1678

Title: Signal subspace algorithms for direction of arrival estimation in the presence of a class of unknown noise fields
Authors: Prasad, S
Chandna, B
Keywords: compute signal
noise covariance
eigenvalues and eigenvectors
simpler orthogonal
eigendecomposition requires
Issue Date: 1988
Citation: Acoustics, Speech, and Signal Processing, 5, 2913 - 2916
Abstract: The authors propose a technique to compute signal bearings for the situation when the desired signal is corrupted by additive noise with unknown covariance. The noise covariance matrix is assumed to be a banded symmetric Toeplitz matrix. This algorithm eliminates the need for the evaluation of eigenvalues and eigenvectors. The algorithm is also computationally very efficient, since it requires the use of a simpler orthogonal decomposition, i.e. only the Householder decomposition. The number of computations required to perform this decomposition is of the order of O(2N3/3), while the eigendecomposition requires O(N4) computations
URI: http://eprint.iitd.ac.in/dspace/handle/2074/1678
Appears in Collections:Electrical Engineering

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