Direction of Arrival (DOA)Estimation based on Sparsity-Aware Signal Processing, M.Sc. Thesis Sharif University of Technology ; Behnia, Fereidoon (Supervisor) ; Babaiezadeh, Massoud (Supervisor)
Abstract
Estimating direction of arrival (DOA) is one of the most important problems in array signal processing to solve which various methods have been proposed. The older methods for estimating signal DOA were divided into three main groups: beamforming, maximum likelihood-based and subspace-based methods. By applying sparse representation techniques to the DOA estimation problem, a new group of methods for solving this problem are introduced. In this thesis, two grid-based methods, which are tow sub groups of sparse methods for estimation of DOA, are proposed. Each of these methods uses singular value decomposition to reduce the power of noise. Also proposed methods are compared with the multiple...
Cataloging briefDirection of Arrival (DOA)Estimation based on Sparsity-Aware Signal Processing, M.Sc. Thesis Sharif University of Technology ; Behnia, Fereidoon (Supervisor) ; Babaiezadeh, Massoud (Supervisor)
Abstract
Estimating direction of arrival (DOA) is one of the most important problems in array signal processing to solve which various methods have been proposed. The older methods for estimating signal DOA were divided into three main groups: beamforming, maximum likelihood-based and subspace-based methods. By applying sparse representation techniques to the DOA estimation problem, a new group of methods for solving this problem are introduced. In this thesis, two grid-based methods, which are tow sub groups of sparse methods for estimation of DOA, are proposed. Each of these methods uses singular value decomposition to reduce the power of noise. Also proposed methods are compared with the multiple...
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