Multiple and single snapshot compressive beamforming

TitleMultiple and single snapshot compressive beamforming
Publication TypeJournal Article
Year of Publication2015
AuthorsGerstoft P, Xenaki A., Mecklenbrauker C.F
JournalJournal of the Acoustical Society of America
Date Published2015/10
Type of ArticleArticle
ISBN Number0001-4966
Accession NumberWOS:000368186600017
Keywordsfrequency-domain; inversion; lasso; location; path; selection; shallow-water; source localization; sparsity

For a sound field observed on a sensor array, compressive sensing (CS) reconstructs the direction of arrival (DOA) of multiple sources using a sparsity constraint. The DOA estimation is posed as an underdetermined problem by expressing the acoustic pressure at each sensor as a phase-lagged superposition of source amplitudes at all hypothetical DOAs. Regularizing with an l(1)-norm constraint renders the problem solvable with convex optimization, and promoting sparsity gives high-resolution DOA maps. Here the sparse source distribution is derived using maximum a posteriori estimates for both single and multiple snapshots. CS does not require inversion of the data covariance matrix and thus works well even for a single snapshot where it gives higher resolution than conventional beamforming. For multiple snapshots, CS outperforms conventional high-resolution methods even with coherent arrivals and at low signal-to-noise ratio. The superior resolution of CS is demonstrated with vertical array data from the SWellEx96 experiment for coherent multi-paths. (C) 2015 Acoustical Society of America.

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