Path Identification in Passive Acoustic Tomography via Time Delay Difference Comparison and Accumulation Analysis
Empirical green’s functions (EGFs) can be extracted from the cross-correlation of ambient ocean noise and serve as the foundation for passive ocean acoustic tomography (POAT). A critical challenge in POAT is the accurate identification of propagation paths, especially in shallow water and short-range scenarios where multipath arrivals often overlap. Traditional methods relying on absolute arrival time delays are rather sensitive to environmental variability and measurement uncertainty. In this study, we propose a path identification method based on time delay differences between extracted acoustic paths, which exhibit lower sensitivity to sound speed profile (SSP) perturbations than absolute time delays. This approach provides a more robust and stable metric for distinguishing coherent arrivals. We further analyze how accumulation time and hydrophone spacing influence the extraction of coherent wavefronts and identify trade-offs in resolution and stability. The effectiveness of the proposed method is validated through both field experiments and Bellhop simulations, demonstrating consistent time delay difference patterns and improved arrival stability. The findings suggest that time delay difference-based path identification enhances robustness and provides practical guidance for optimizing POAT deployments in complex shallow water environments.
Authors
- Wen Qiang Xu (ORCID: https://orcid.org/0000-0001-9138-8773)
- Ting Zhang (ORCID: https://orcid.org/0000-0002-9440-3219)
- T. Ma (ORCID: https://orcid.org/0009-0001-4979-6666)
Institutions
- Zhejiang Ocean University (CN)
- Institute of Deep-Sea Science and Engineering (CN)
- Zhejiang University (CN)
Publication Details
- Journal
- Journal of Marine Science and Engineering
- Published
- 2025-10-17
- DOI
- https://doi.org/10.3390/jmse13101996
- Citations
- 1
- Primary Topic
- Seismic Waves and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 1.87