A Virtual-Beacon-Based Calibration Method for Precise Acoustic Positioning of Deep-Sea Sensing Networks

The rapid expansion of deep-sea sensing networks underscores the critical need for accurate underwater positioning of observation base stations. However, achieving precise acoustic localization, particularly at depths exceeding 4 km, remains a significant challenge due to systematic ranging errors, clock drift, and inaccuracies in sound speed modeling. This study proposes and validates a three-tier calibration framework consisting of a Dynamic Single-Difference (DSD) solver, a geometrically optimized reference buoy selection algorithm, and a Virtual Beacon (VB) depth inversion method based on sound speed profiles. Through simulations under varying noise conditions, the DSD method effectively mitigates common ranging and clock errors. The geometric reference optimization algorithm enhances the selection of optimal buoy layouts and reference points. At a depth of 4 km, the VB method improves vertical positioning accuracy by 15% compared to the DSD method alone, and nearly doubles vertical accuracy compared to traditional non-differential approaches. This research demonstrates that deep-sea underwater target calibration can be achieved without high-precision time synchronization and in the presence of fixed ranging errors. The proposed framework has the potential to lower technological barriers for large-scale deep-sea network deployments and provides a robust foundation for autonomous deep-sea exploration.

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Publication Details

Journal
Journal of Marine Science and Engineering
Published
2025-07-25
DOI
https://doi.org/10.3390/jmse13081422
Primary Topic
Underwater Vehicles and Communication Systems
Type
article
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article

A Virtual-Beacon-Based Calibration Method for Precise Acoustic Positioning of Deep-Sea Sensing Networks

Wei Wu, Binjian Shen, Yuqi Zhu, Biyuan Yao
Journal of Marine Science and Engineering
Underwater Vehicles and Communication Systems
article

A Virtual-Beacon-Based Calibration Method for Precise Acoustic Positioning of Deep-Sea Sensing Networks

Wei Wu, Binjian Shen, Yuqi Zhu, Biyuan Yao
article en

Abstract

The rapid expansion of deep-sea sensing networks underscores the critical need for accurate underwater positioning of observation base stations. However, achieving precise acoustic localization, particularly at depths exceeding 4 km, remains a significant challenge due to systematic ranging errors, clock drift, and inaccuracies in sound speed modeling. This study proposes and validates a three-tier calibration framework consisting of a Dynamic Single-Difference (DSD) solver, a geometrically optimized reference buoy selection algorithm, and a Virtual Beacon (VB) depth inversion method based on sound speed profiles. Through simulations under varying noise conditions, the DSD method effectively mitigates common ranging and clock errors. The geometric reference optimization algorithm enhances the selection of optimal buoy layouts and reference points. At a depth of 4 km, the VB method improves vertical positioning accuracy by 15% compared to the DSD method alone, and nearly doubles vertical accuracy compared to traditional non-differential approaches. This research demonstrates that deep-sea underwater target calibration can be achieved without high-precision time synchronization and in the presence of fixed ranging errors. The proposed framework has the potential to lower technological barriers for large-scale deep-sea network deployments and provides a robust foundation for autonomous deep-sea exploration.

Journal of Marine Science and EngineeringVol. 13(8)
Chinese Academy of Sciences (CN), Hainan University (CN), Sanya University (CN), Institute of Deep-Sea Science and Engineering (CN), University of Chinese Academy of Sciences (CN), Zhejiang University (CN)
Life below water
Openalex Percentile: Top 75%
Underwater Vehicles and Communication Systems
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A Virtual-Beacon-Based Calibration Method for Precise Acoustic Positioning of Deep-Sea Sensing Networks — Wei Wu, Binjian Shen, et al. · Journal of Marine Science and Engineering (2025) | TGRS Research Map | TGRS