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

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.