Bound on the estimation grid size for sparse reconstruction in direction of arrival estimation

Mario Coutiño, Radmila Pribic, Geert Leus

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Abstract

A bound for sparse reconstruction involving both the signal-to-noise ratio (SNR) and the estimation grid size is presented. The bound is illustrated for the case of a uniform linear array (ULA). By reducing the number of possible sparse vectors present in the feasible set of a constrained ℓ1-norm minimization problem, ambiguities in the reconstruction of a single source under noise can be reduced. This reduction is achieved by means of a proper selection of the estimation grid, which is naturally linked with the mutual coherence of the sensing matrix. Numerical simulations show the performance of sparse reconstruction with an estimation grid meeting the provided bound demonstrating the effectiveness of the proposed bound.
Original languageEnglish
Title of host publication2016 IEEE Statistical Signal Processing Workshop (SSP)
Place of PublicationPiscataway, NJ
PublisherIEEE
Pages1-4
Number of pages4
ISBN (Print)978-1-4673-7802-4
DOIs
Publication statusPublished - 25 Aug 2016
Event2016 IEEE Statistical Signal Processing Workshop (SSP) - Palma de Mallorca, Spain
Duration: 26 Jun 201629 Jun 2017
http://ssp2016.tsc.uc3m.es/

Workshop

Workshop2016 IEEE Statistical Signal Processing Workshop (SSP)
Abbreviated titleSSP 2016
CountrySpain
CityPalma de Mallorca
Period26/06/1629/06/17
Internet address

Keywords

  • sparse reconstruction
  • direction of arrival (DOA) estimation
  • sensing matrix
  • uniform linear array
  • compressed sensing

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