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Improvement in matched field processing using the CLEAN algorithm.

H C Song1, J de Rosny, W A Kuperman

  • 1Marine Physical Laboratory, Scripps Institute of Oceanography, University of California-San Diego, La Jolla, California 92093-0238, USA.

The Journal of the Acoustical Society of America
|March 27, 2003
PubMed
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The CLEAN algorithm enhances matched field processing for improved source localization. This method effectively suppresses sidelobes, aiding in the detection of weak sources masked by stronger ones.

Area of Science:

  • Ocean acoustics
  • Signal processing
  • Array processing

Background:

  • Adaptive matched field processing (MFP), like the minimum variance distortionless processor (MV), excels at sidelobe suppression in source localization with accurate environmental knowledge.
  • Robust adaptive algorithms, such as the white noise constraint (WNC), are used to mitigate mismatch issues but often compromise sidelobe control.

Purpose of the Study:

  • To extend the CLEAN algorithm from radio astronomy to matched field processing.
  • To improve the performance of matched field processing, particularly in scenarios with strong interfering sources.

Main Methods:

  • The study extends the CLEAN algorithm, originally developed for radio astronomy, to the domain of matched field processing.
  • The performance of the combined CLEAN and MFP approach is evaluated through numerical simulations and experimental data analysis.

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Main Results:

  • Matched field processing combined with the CLEAN algorithm demonstrates improved performance in source localization.
  • This integrated approach is particularly effective in scenarios where a weak source is obscured by the sidelobes of a much stronger source.

Conclusions:

  • The CLEAN algorithm offers a valuable enhancement to matched field processing for source localization.
  • The integration of CLEAN improves the ability to detect weak signals in complex acoustic environments by effectively managing sidelobe artifacts.