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Multiplane deconvolution in underwater acoustics: Simultaneous estimations of source level and position.

Maxime Polichetti1, Valentin Baron1, Jérôme I Mars1

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A new CLEAN deconvolution method improves acoustic imaging by enabling simultaneous localization and source level estimation, overcoming limitations of conventional beamforming (CBF). This technique reduces artifacts for clearer underwater acoustic source identification.

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Area of Science:

  • Oceanography
  • Acoustics
  • Signal Processing

Background:

  • Conventional beamforming (CBF) in acoustic imaging struggles with simultaneous accurate positioning and source level estimation.
  • CBF-generated acoustic maps often contain artifacts due to broad point-spread functions.

Purpose of the Study:

  • To introduce an enhanced CLEAN deconvolution procedure for improved acoustic source localization and characterization.
  • To address limitations in simultaneous localization, source level estimation, and artifact reduction in acoustic imaging.

Main Methods:

  • Developed an original CLEAN deconvolution algorithm incorporating an out-of-plane source plane.
  • Applied the method to experimental data simulating a deep-sea mining scenario with a distant acoustic source and interfering boat noise.

Main Results:

  • The proposed CLEAN deconvolution achieved simultaneous localization and source level estimation.
  • The method effectively reduced artifacts present in conventional beamforming acoustic maps.
  • Demonstrated successful application in a challenging deep-sea acoustic environment.

Conclusions:

  • The enhanced CLEAN deconvolution procedure offers a robust solution for simultaneous acoustic source localization, level estimation, and de-noising.
  • This approach significantly improves the quality of acoustic maps compared to conventional beamforming.
  • The technique is particularly valuable for complex underwater acoustic imaging applications, such as deep-sea mining.