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Underdetermined DOA Estimation Using MVDR-Weighted LASSO


Underdetermined DOA Estimation Using MVDR-Weighted LASSO

Salama, Amgad A., Ahmad, M. Omair and Swamy, M. N. S. (2016) Underdetermined DOA Estimation Using MVDR-Weighted LASSO. Sensors, 16 (9). p. 1549. ISSN 1424-8220

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Official URL: http://dx.doi.org/10.3390/s16091549


The direction of arrival (DOA) estimation problem is formulated in a compressive sensing (CS) framework, and an extended array aperture is presented to increase the number of degrees of freedom of the array. The ordinary least square adaptable least absolute shrinkage and selection operator (OLS A-LASSO) is applied for the first time for DOA estimation. Furthermore, a new LASSO algorithm, the minimum variance distortionless response (MVDR) A-LASSO, which solves the DOA problem in the CS framework, is presented. The proposed algorithm does not depend on the singular value decomposition nor on the orthogonality of the signal and the noise subspaces. Hence, the DOA estimation can be done without a priori knowledge of the number of sources. The proposed algorithm can estimate up to ((M2−2)/2+M−1)/2 sources using M sensors without any constraints or assumptions about the nature of the signal sources. Furthermore, the proposed algorithm exhibits performance that is superior compared to that of the classical DOA estimation methods, especially for low signal to noise ratios (SNR), spatially-closed sources and coherent scenarios.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Electrical and Computer Engineering
Item Type:Article
Authors:Salama, Amgad A. and Ahmad, M. Omair and Swamy, M. N. S.
Journal or Publication:Sensors
  • Concordia Open Access Author Fund
Digital Object Identifier (DOI):10.3390/s16091549
Keywords:adaptable LASSO; sparse array; direction of arrival estimation; compressive sensing; sensor array processing
ID Code:982272
Deposited By: Danielle Dennie
Deposited On:21 Mar 2017 18:26
Last Modified:18 Jan 2018 17:54
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