车载SINS/1D-LDV杆臂误差在线标定算法
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国防科技大学前沿交叉学科学院

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TN249

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湖南省自然科学基金(激光测速仪在线标定技术及其在车载自主导航系统中的应用,2021JJ30782);


Online calibration algorithm of Vehicle-mounted SINS/1D-LDV Lever-Arm error
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    摘要:

    针对在一维激光多普勒测速仪(one-dimensional Laser Doppler Velocimeter, 1D-LDV)和捷联惯导系统(Strapdown Inertial Navigation System, SINS)构成的车载组合导航系统中,1D-LDV和SINS的量测速度间由于两者安装位置不同存在杆臂速度误差的问题,提出了一种Kalman滤波在线标定算法对安装杆臂进行标定并补偿。通过引入在载体行进过程中速度方向始终保持载体行进方向的点,对传统杆臂速度误差模型进行了改进,使其能够准确反映1D-LDV与SINS输出的量测速度间的真实关系。车载实验结果表明,该标定算法能够有效标定1D-LDV与SINS间的杆臂误差。将经过杆臂误差补偿的1D-LDV量测速度与SINS的陀螺数据进行航迹推算,两组实验所得水平定位误差由8.80m和6.60m分别降至7.07m和5.48m,在一定程度上提高了导航定位精度。

    Abstract:

    Aiming at the problem that the lever-arm velocity error between the measured speeds of one-dimensional Laser Doppler Velocimeter (1D-LDV) and Strapdown Inertial Navigation System (SINS) caused by their different installation positions in the vehicle-mounted integrated navigation systems composed of 1D-LDV and SINS, an online calibration algorithm based on Kalman filter is proposed to calibrate and compensate the mounting lever-arm. By introducing a reference point that maintains alignment between the velocity direction and the carrier's direction of motion during movement, the traditional lever-arm velocity error model was improved, so that it can accurately characterize the actual relationship between the measured velocities from the 1D-LDV and SINS. The vehicle experiment results show that the calibration algorithm can effectively calibrate the arm error between 1D-LDV and SINS. By using the 1D-LDV measured velocity (after lever-arm error compensation) and the gyroscopic data from the SINS to perform dead reckoning, the horizontal positioning errors in two experimental trials are reduced from 8.80 m and 6.60 m to 7.07 m and 5.48 m respectively, demonstrating a moderate improvement in navigation and positioning accuracy.

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  • 收稿日期:2025-01-19
  • 最后修改日期:2025-06-12
  • 录用日期:2025-05-06
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