Block-sparse beamforming for spatially extended sources in a Bayesian formulation

Angeliki Xenaki, Efren Fernandez Grande, Peter Gerstoft

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Direction-of-arrival (DOA) estimation refers to the localization of sound sources on an angular grid from noisy measurements of the associated wavefield with an array of sensors. For accurate localization, the number of angular look-directions is much larger than the number of sensors, hence, the problem is underdetermined and requires regularization. Traditional methods use an L2-norm regularizer, which promotes minimum-power (smooth) solutions, while regularizing with L1-norm promotes sparsity. Sparse signal reconstruction improves the resolution in DOA estimation in the presence of a few point sources, but cannot capture spatially extended sources. The DOA estimation problem is formulated in a Bayesian framework where regularization is imposed through prior information on the source spatial distribution which is then reconstructed as the maximum a posteriori estimate. A composite prior is introduced, which simultaneously promotes a piecewise constant profile and sparsity in the solution. Simulations and experimental measurements show that this choice of regularization provides high-resolution DOA estimation in a general framework, i.e., in the presence of spatially extended sources.
Original languageEnglish
JournalJournal of the Acoustical Society of America
Issue number3
Pages (from-to)1828-1838
Publication statusPublished - 2016


  • Arts and Humanities (miscellaneous)
  • Acoustics and Ultrasonics
  • Bayesian networks
  • Signal reconstruction
  • Bayesian formulation
  • Bayesian frameworks
  • Direction of arrivalestimation(DOA)
  • High resolution DOA estimation
  • Maximum a posteriori estimates
  • Noisy measurements
  • Piece-wise constants
  • Sparse signal reconstruction
  • Direction of arrival
  • Acoustic signal processing
  • Probability theory, stochastic processes, and statistics
  • Signal processing and detection
  • Other topics in statistics
  • acoustic radiators
  • acoustic signal processing
  • array signal processing
  • Bayes methods
  • direction-of-arrival estimation
  • piecewise constant techniques
  • piecewise constant profile
  • composite prior
  • maximum-a-posteriori estimate
  • source spatial distribution
  • Bayesian framework
  • sparse signal reconstruction
  • array of sensors
  • angular grid
  • sound source localization
  • spatially extended sources
  • block-sparse beamforming

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