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Proceedings Paper

Joint sparsity models for wideband array processing
Author(s): Petros T. Boufounos; Paris Smaragdis; Bhiksha Raj
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Paper Abstract

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.

Paper Details

Date Published: 27 September 2011
PDF: 10 pages
Proc. SPIE 8138, Wavelets and Sparsity XIV, 81380K (27 September 2011); doi: 10.1117/12.893870
Show Author Affiliations
Petros T. Boufounos, Mitsubishi Electric Research Labs. (United States)
Paris Smaragdis, Univ. of Illinois at Urbana-Champaign (United States)
Bhiksha Raj, Carnegie Mellon Univ. (United States)

Published in SPIE Proceedings Vol. 8138:
Wavelets and Sparsity XIV
Manos Papadakis; Dimitri Van De Ville; Vivek K. Goyal, Editor(s)

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