Joint sparsity models for wideband array processing

Petros T. Boufounos, Paris Smaragdis, Bhiksha Raj

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Recent work has demonstrated the power of sparse models and representations in signal processing applications and has provided the community with computational tools to use it. In this paper we explore the use of sparsity in localization and beamforming when capturing multiple broadband sources using a sensor array. Specifically, we reformulate the wideband signal acquisition as a joint/group sparsity problem in a combined frequency-space domain. Under this formulation the signal is sparse in the spatial domain but has common support in all frequencies. Using techniques from the model-based compressive sensing literature we demonstrate that it is possible to robustly capture, localize and often reconstruct multiple signals present in the scene.

Original languageEnglish (US)
Title of host publicationWavelets and Sparsity XIV
StatePublished - 2011
EventWavelets and Sparsity XIV - San Diego, CA, United States
Duration: Aug 21 2011Aug 24 2011

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X


OtherWavelets and Sparsity XIV
Country/TerritoryUnited States
CitySan Diego, CA


  • block sparsity
  • broadband array processing
  • compressive sensing
  • joint sparsity
  • localization
  • microphone array

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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