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Spatial domain dedispersion transform and its application extracting horizontal wavenumber structure.

Hongchen Zhang1,2, Shihong Zhou1,2, Changpeng Liu2

  • 1University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China.

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|August 15, 2024
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Summary
This summary is machine-generated.

This study introduces a novel method for analyzing shallow water acoustics, extracting crucial waveguide and source information from complex sound fields. The technique enhances acoustic inversion capabilities, even with limited array sizes and low signal quality.

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Area of Science:

  • Underwater acoustics
  • Signal processing
  • Geophysical exploration

Background:

  • Shallow water acoustic fields are complex due to dispersion and multipath effects.
  • This complexity holds vital information about the underwater environment and acoustic sources.
  • Extracting horizontal wavenumber and mode amplitudes is key for acoustic inversion but limited by array constraints.

Purpose of the Study:

  • To develop a method for extracting acoustic mode information from shallow water environments.
  • To overcome limitations of small aperture arrays and low signal-to-noise ratios in acoustic inversion.
  • To validate a new spatial domain dedispersion transform and frequency domain accumulation approach.

Main Methods:

  • Proposed spatial domain dedispersion transform and frequency domain accumulation.
  • Leveraged broadband sources with known or slowly varying phase spectra.
  • Validated the approach on dual-hydrophone horizontal arrays, relaxing signal-to-noise ratio constraints.

Main Results:

  • Theoretical proof of algorithm performance provided.
  • Analysis of parameter impacts: acoustic source bandwidth, array element count, and aperture.
  • Effectiveness validated through simulations and experimental data.

Conclusions:

  • The proposed method successfully extracts crucial acoustic information in challenging shallow water conditions.
  • The technique offers a viable solution for acoustic inversion with small aperture and low SNR arrays.
  • Validated algorithms demonstrate robustness and applicability to real-world acoustic data.