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Updated: Jul 2, 2026
08:54
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 Cui1,2, 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 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.
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.
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