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,spatiot...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 Profle(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 fnally develop an adaptive two-stage information flter to estimate sound speed perturbation and detect USBL outliers.Simulations and South China Sea trials are conducted to verify its efectiveness.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 efectively estimates the sound speed disturbance in real time,thereby signifcantly improving the performance of tightly integrated inertial-acoustic navigation systems.展开更多
基金National Natural Science Foundation of China(42304040,42174020,42174021)National Key Research and Development Program of China(No.2024YFB3909700,2024YFB3909702)+3 种基金Shandong Province Natural Science Foundation(ZR2023QD081,ZR2025MS643)National Key Laboratory of Spatial Datum(No.SKLSD2025-KF-16)Fundamental Research Funds for the Central Universities(No.24CX06045A)Qingdao Natural Science Foundation(23-2-1-65-zyyd-jch,23-2-1-217-zyyd-jch).
文摘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 Profle(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 fnally develop an adaptive two-stage information flter to estimate sound speed perturbation and detect USBL outliers.Simulations and South China Sea trials are conducted to verify its efectiveness.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 efectively estimates the sound speed disturbance in real time,thereby signifcantly improving the performance of tightly integrated inertial-acoustic navigation systems.
