Broadband underwater localization of multiple sources using basis pursuit de-noising

Chunshan Liu*, Yuriy V. Zakharov, Teyan Chen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

50 Citations (Scopus)

Abstract

Locating multiple underwater acoustic sources is a problem that can be solved using antenna array beamforming based on the matched field (MF) processing. However, known MF beamforming techniques fail to provide good performance for multiple sources, a high noise power, and/or when the sources are close to each other. This paper proposes an MF technique for solving the localization problem. The proposed technique exploits formulation of the localization problem in terms of sparse representation of a small number of source positions among a much larger number of potential positions. The sparse representation is formulated as the basis pursuit de-noising (BPDN) problem for complex-valued variables. The solution is found as a joint solution to a set of BPDN problems corresponding to the set of source frequencies subject to the joint support. The joint BPDN problem is efficiently solved using the Homotopy approach and coordinate descent search. For further reduction in the complexity, a position grid refinement method is applied. Using simulated and real experimental data, it is shown that the technique can provide accurate source localization for multiple sources. The proposed technique outperforms other MF techniques in resolving sources positioned closely to each other, tolerance to the noise and capability of locating multiple sources.

Original languageEnglish
Article number6112249
Pages (from-to)1708-1717
Number of pages10
JournalIEEE Transactions on Signal Processing
Volume60
Issue number4
DOIs
Publication statusPublished - Apr 2012
Externally publishedYes

Keywords

  • Basis pursuit de-noising (BPDN)
  • coordinate descent
  • homotopy
  • matched-field (MF) processing
  • multisource localization
  • sparse representation
  • underwater acoustics

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