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Shallow-water sparsity-cognizant source-location mapping.

Pedro A Forero1, Paul A Baxley1

  • 1Maritime Systems Division, Space and Naval Warfare Systems Center Pacific, 53560 Hull Street, San Diego, California 92152.

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Summary

This study introduces a new method for underwater acoustic source localization in shallow waters. The technique reduces ambiguities and improves accuracy, even in noisy conditions, outperforming traditional matched-field processing.

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Area of Science:

  • Ocean acoustics
  • Signal processing
  • Geophysics

Background:

  • Underwater acoustic source localization in shallow waters is complex due to environmental factors.
  • Matched-field processing (MFP) is a common technique but suffers from artifacts, limiting source localization accuracy.
  • Existing methods struggle with ambiguity and reduced resolution, especially at low signal-to-noise ratios.

Purpose of the Study:

  • To develop a robust and accurate method for shallow-water acoustic source localization.
  • To overcome the limitations of traditional Matched-Field Processing (MFP) by addressing artifacts and improving resolution.
  • To leverage the sparse structure of the localization problem and acoustic propagation models for enhanced performance.

Main Methods:

  • The study formulates the underwater acoustic source-localization problem as a sparsity-inducing stochastic optimization problem.
  • A novel scheme is introduced that exploits the sparse structure and employs an acoustic propagation environment model.
  • An iterative solver based on block-coordinate descent is developed for efficient computation.

Main Results:

  • The proposed method generates a source-location map (SLM) with significantly reduced ambiguities and improved resolution compared to classical MFP.
  • The technique demonstrates robustness against model mismatch, a common issue in acoustic propagation modeling.
  • Effective localization performance is achieved even at low signal-to-noise ratios.

Conclusions:

  • The developed sparsity-based optimization scheme offers a robust and high-resolution solution for shallow-water acoustic source localization.
  • This approach enhances the capabilities of passive sonar systems in challenging underwater environments.
  • The method provides a significant advancement over conventional Matched-Field Processing techniques.