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Compressive beamforming

TitleCompressive beamforming
Publication TypeJournal Article
Year of Publication2014
AuthorsXenaki A., Gerstoft P, Mosegaard K.
JournalJournal of the Acoustical Society of America
Date Published2014/07
Type of ArticleArticle
ISBN Number0001-4966
Accession NumberWOS:000339163800034
Keywordsarray; localization; noise; projections; random matrices; restricted isometry property; source; sparse signal reconstruction

Sound source localization with sensor arrays involves the estimation of the direction-of-arrival (DOA) from a limited number of observations. Compressive sensing (CS) solves such underdetermined problems achieving sparsity, thus improved resolution, and can be solved efficiently with convex optimization. The DOA estimation problem is formulated in the CS framework and it is shown that CS has superior performance compared to traditional DOA estimation methods especially under challenging scenarios such as coherent arrivals and single-snapshot data. An offset and resolution analysis is performed to indicate the limitations of CS. It is shown that the limitations are related to the beampattern, thus can be predicted. The high-resolution capabilities and the robustness of CS are demonstrated on experimental array data from ocean acoustic measurements for source tracking with single-snapshot data. (C) 2014 Acoustical Society of America.

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