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Related Experiment Video

Updated: Jul 2, 2026

Measurements of Waves in a Wind-wave Tank Under Steady and Time-varying Wind Forcing

Measurements of Waves in a Wind-wave Tank Under Steady and Time-varying Wind Forcing

Published on: February 13, 2018

Quantifying time-varying wind-driven effects on matched-field localization: Mechanisms and a physics-coupled Bayesian

Xiaoming Cui^1,2, Qing Hu², Huayong Yang¹

¹Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou, Guangdong 511458, China.

The Journal of the Acoustical Society of America

|July 1, 2026

Summary

This summary is machine-generated.

This study introduces a physics-coupled particle filter (PC-PF) to improve underwater acoustic source tracking in dynamic ocean environments. The PC-PF effectively reduces range errors caused by wind-driven changes, outperforming traditional methods.

Related Experiment Videos

Last Updated: Jul 2, 2026

Measurements of Waves in a Wind-wave Tank Under Steady and Time-varying Wind Forcing

Measurements of Waves in a Wind-wave Tank Under Steady and Time-varying Wind Forcing

Published on: February 13, 2018

Area of Science:

Oceanography
Acoustics
Signal Processing

Background:

Matched-field processing is sensitive to environmental variations.
Existing methods often overlook time-evolving ocean conditions like wind-driven changes.

Purpose of the Study:

To investigate the impact of dynamic environmental changes on acoustic propagation.
To develop an adaptive algorithm for robust source localization in time-varying shallow-water environments.

Main Methods:

Introduced a conditional modal phase-spread analysis to quantify environmental degradation.
Developed a physics-coupled particle filter (PC-PF) integrating a reduced-order environmental model.
Utilized broadband numerical experiments to evaluate performance.

Main Results:

Wind-driven mixed-layer deepening causes significant phase errors and range bias in conventional processors.
The PC-PF significantly reduced root mean square error and maintained track continuity.
Demonstrated dependency of performance on wind state, range, frequency, and source depth.

Conclusions:

The PC-PF offers a robust framework for dynamic environmental adaptation in underwater acoustics.
Accurate source tracking is achievable even with evolving oceanographic conditions.
The proposed method enhances acoustic signal processing in complex, time-varying scenarios.