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<p>Autonomous and Remotely-operated Vehicles (ARVs) rely on precise underwater navigation via integrated Ultra-Short Baseline (USBL) acoustic positioning system and Strap-down Inertial Navigation System (SINS). However, spatiotemporal variations in underwater Sound Speed Profile (SSP) degrade USBL performance, reducing overall navigation accuracy. This study proposes a novel in-situ SSP correction scheme for SINS/USBL integration. We analyze SSP temporal variation with the USBL positioning scheme to build a Two Dimensional (2D) temporal SSP model; then derive partial derivatives (based on equal-gradient ray-tracing) to quantify the displacements from azimuth, incident angle, and propagation time errors; and finally develop an adaptive two-stage information filter to estimate sound speed perturbation and detect USBL outliers. Simulations and South China Sea trials are conducted to verify its effectiveness. Compared with the traditional tight-coupling method, root mean square errors are reduced from 0.45m and 0.23&#xa0;m with the traditional tightly-coupled method to 0.08&#xa0;m and 0.07 m with the in-situ SSP correction scheme, representing improvements of 82.2% in the north and 69.6% in the east directions, respectively. Experimental results demonstrate that the proposed method effectively estimates the sound speed disturbance in real time, thereby significantly improving the performance of tightly integrated inertial-acoustic navigation systems.</p>

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An in-situ sound speed profile correction scheme for the tight-coupling integration of SINS/USBL in deep-sea ARV navigation

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年12月3日

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  • Huimin Liu,
  • Shuang Zhao,
  • Zhenjie Wang,
  • Jixiang Zhou,
  • Kai Du,
  • Rui Shan

摘要

Autonomous and Remotely-operated Vehicles (ARVs) rely on precise underwater navigation via integrated Ultra-Short Baseline (USBL) acoustic positioning system and Strap-down Inertial Navigation System (SINS). However, spatiotemporal variations in underwater Sound Speed Profile (SSP) degrade USBL performance, reducing overall navigation accuracy. This study proposes a novel in-situ SSP correction scheme for SINS/USBL integration. We analyze SSP temporal variation with the USBL positioning scheme to build a Two Dimensional (2D) temporal SSP model; then derive partial derivatives (based on equal-gradient ray-tracing) to quantify the displacements from azimuth, incident angle, and propagation time errors; and finally develop an adaptive two-stage information filter to estimate sound speed perturbation and detect USBL outliers. Simulations and South China Sea trials are conducted to verify its effectiveness. Compared with the traditional tight-coupling method, root mean square errors are reduced from 0.45m and 0.23 m with the traditional tightly-coupled method to 0.08 m and 0.07 m with the in-situ SSP correction scheme, representing improvements of 82.2% in the north and 69.6% in the east directions, respectively. Experimental results demonstrate that the proposed method effectively estimates the sound speed disturbance in real time, thereby significantly improving the performance of tightly integrated inertial-acoustic navigation systems.