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Related Experiment Video

Updated: Oct 21, 2025

A Field Primer for Monitoring Benthic Ecosystems Using Structure-From-Motion Photogrammetry
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Probabilistic focalization for shallow water localization.

Florian Meyer1, Kay L Gemba2

  • 1Scripps Institution of Oceanography and Department of Electrical and Computer Engineering, University of California at San Diego, La Jolla, California 92093, USA.

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|September 2, 2021
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Summary
This summary is machine-generated.

This study introduces a new Bayesian method for pinpointing underwater acoustic sources in shallow waters. The approach improves tracking accuracy, even with uncertain environmental conditions, outperforming existing techniques.

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Area of Science:

  • Acoustics
  • Signal Processing
  • Oceanography

Background:

  • Accurate localization of underwater acoustic sources is crucial for maritime situational awareness.
  • Passive acoustic localization in shallow water presents significant challenges due to complex environmental factors.

Purpose of the Study:

  • To develop a sequential Bayesian estimation method for passive acoustic source localization in shallow water.
  • To enhance the robustness of source localization under environmental uncertainty.

Main Methods:

  • A probabilistic focalization approach is proposed, associating detected directions of arrival (DOAs) with modeled DOAs.
  • The method jointly estimates the time-varying source location using embedded ray tracing.
  • Environmental parameters characterizing the acoustic waveguide are incorporated into the model.

Main Results:

  • The proposed method demonstrates performance advantages over matched field processing.
  • Robustness in scenarios with severe environmental uncertainty is achieved due to the statistical model.
  • Validation was performed using data from the SWellEx-96 experiment.

Conclusions:

  • The sequential Bayesian estimation method offers a robust and accurate solution for passive acoustic source localization in shallow water.
  • The probabilistic focalization approach effectively handles environmental variability.
  • This technique advances maritime situational awareness capabilities.