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Related Experiment Video

Updated: Jul 11, 2025

Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method
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Multifrequency matched-field source localization based on Wasserstein metric for probability measures.

Qixuan Zhu1, Chao Sun1, Mingyang Li1

  • 1School of Marine Science and Technology, Northwestern Polytechnical University, Xi'an, China.

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|November 14, 2023
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Summary
This summary is machine-generated.

This study introduces a Wasserstein processor for underwater source localization, improving accuracy by using a statistical metric on cross-spectral density matrices. The method effectively reduces ambiguity and enhances localization, even with limited data.

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Area of Science:

  • Acoustics
  • Signal Processing
  • Statistical Inference

Background:

  • Matched-field processing (MFP) is a generalized beamforming technique for underwater source localization.
  • Traditional MFP relies on correlating array data with replica vectors.
  • Existing methods face challenges with ambiguity and performance under limited data conditions.

Purpose of the Study:

  • To reformulate the Matched-field processing scheme using a statistical metric.
  • To develop a novel Wasserstein processor for enhanced underwater source localization.
  • To improve robustness and reduce ambiguity in source localization, especially with deficient snapshots.

Main Methods:

  • Reformulation of MFP by computing a statistical metric between Gaussian probability measures of cross-spectral density matrices (CSDMs).
  • Application of the Wasserstein metric to develop a processor that leverages intrinsic properties of CSDMs.
  • Derivation of a multifrequency processor and an approach to derive the averaged Bartlett processor using Wasserstein metric on Dirac measures.

Main Results:

  • The Wasserstein processor effectively suppresses ambiguities and distinguishes multiple sources.
  • A multifrequency Wasserstein processor improves localization statistics with deficient snapshots.
  • Demonstrated effectiveness and robustness through acoustic simulations and the SWellEx-96 experiment data, showing reduced ambiguity.

Conclusions:

  • The Wasserstein metric provides an innovative and effective approach for Matched-field processing in underwater acoustics.
  • The developed Wasserstein processor offers improved localization accuracy and ambiguity reduction.
  • This method presents a new perspective for Matched-field processing, including a novel derivation of the averaged Bartlett processor.