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Improving the underwater navigation performance of an IMU with acoustic long baseline calibration

Satellite Navigation 2024年第1期5卷 224-239页

作者： paipai wu Wenfeng Nie Yangfan Liu Tianhe Xu Shandong Key Laboratory of Optical Astronomy and Solar-Terrestrial Environment Institute of Space SciencesShandong UniversityWeihai264209ShandongChina Research Group of Astronomy and Geomatics(gAGE) Universitat Politecnica de Catalunya(UPC)BarcelonaSpain

Underwater acoustic Long-Baseline System(LBL)is an important technique for submarine positioning and ***,the high cost of the seafloor equipment and complex construction of a seafloor network restrict the distribution of the LBL within a small area,making an underwater vehicle difficult for long-distance and high-precision acoustic-based or inertial-based *** therefore propose an acoustic LBL-based Inertial Measurement Unit(IMU)calibration *** the underwater vehicle can receive the acoustic signal from a seafloor beacon,the IMU is precisely calibrated to reduce the cumulative error of Strapdown Inertial Navigation System(SINS).In this way,the IMU is expected to maintain a certain degree of accuracy by relying solely on SINS when the vehicle reaches out the range of the LBL network and cannot receive the acoustic *** present the acoustic LBL-based IMU online calibration model and analyze the factors that affect the accuracy of IMU *** results fulfill the expectation that the gyroscope bias and accelerometer bias are the main error sources that affect the divergence of SINS position errors,and the track line of the underwater vehicle directly affects the accuracy of the calibration *** addition,we deduce that an optimal calibration trajectory needs to consider the effects of the three-dimensional observability and position dilution of *** the experiment,we compare the effects of seven calibration trajectories:straight and diamond-shaped with and without the change of depth,and three sets of curves with the change of depth:circular,S-shaped,and *** them,we find that the figure-eight is the optimal trajectory for acoustic LBL-based IMU online *** take the maintenance period during which the accumulated SINS Three Dimensional(3D)position errors are below 1 km to evaluate the calibration *** filed experimental results show that for the Micro-electromechanical System

关键词： Acoustic LBL Online IMU calibration SINS Relay reference network

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