Sparsity and super-resolution in sound source localization with sensor arrays

Angeliki Xenaki, Peter Gerstoft, Klaus Mosegaard

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

Sound source localization with sensor arrays involves the estimation of the direction-of-arrival (DOA) from a limited number of observations. Compressive sensing (CS) is a method for solving such undetermined problems which achieves simultaneously sparsity, thus super-resolution, and computational speed. We formulate the DOA estimation as a sparse signal reconstruction problem and show that methods which exploit sparsity have superior performance compared to traditional methods for DOA estimation. To demonstrate the high-resolution capabilities and the robustness of CS and other sparsity promoting optimization techniques in DOA estimation, the methods are applied to experimental data from underwater acoustic measurements in the challenging scenario of source tracking from single snapshot data.
Original languageEnglish
Title of host publicationProceedings - 2nd Underwater Acoustics Conference and Exhibition
EditorsJohn S. Papadakis, Leif Bjørnø
Number of pages6
Publication date2014
Pages783-788
ISBN (Electronic)978-618-80725-1-0
Publication statusPublished - 2014
Event2nd international conference and exhibition on Underwater Acoustics - Rhodos, Greece
Duration: 22 Jun 201427 Jun 2014
Conference number: 2

Conference

Conference2nd international conference and exhibition on Underwater Acoustics
Number2
CountryGreece
CityRhodos
Period22/06/201427/06/2014

Keywords

  • Sparsity
  • Compressive sensing
  • Direction of arrival (DOA) estimation
  • Sensor arrays

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