车载SINS/1D-LDV杆臂误差在线标定算法
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作者单位:

1.国防科技大学 前沿交叉学科学院, 湖南 长沙 410073 ; 2.国防科技大学 南湖之光实验室, 湖南 长沙 410073

作者简介:

张涛(2000—),男,四川巴中人,硕士研究生,E-mail:1786384585@qq.com

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中图分类号:

TN249

基金项目:

湖南省自然科学基金资助项目(2021JJ30782)


Online calibration algorithm of vehicle-mounted SINS/1D-LDV lever-arm error
Author:
Affiliation:

1.College of Advanced Interdisciplinary Studies, National University of Defense Technology, Changsha 410073 , China ; 2.Nanhu Laser Laboratory, National University of Defense Technology, Changsha 410073 , China

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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,由于两者安装位置不同存在的杆臂速度误差问题,提出一种卡尔曼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,两组实验所得的水平定位误差由8.80 m和6.60 m分别降至7.07 m和5.48 m,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 1D-LDV (one-dimensional laser Doppler velocimeter) and SINS(strapdown inertial navigation system) 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 was proposed to calibrate and compensate the mounting lever-arm. By introducing a reference point that maintains alignment between the velocity direction and the carriers 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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张涛, 聂晓明, 周健, 等. 车载SINS/1D-LDV杆臂误差在线标定算法[J]. 国防科技大学学报, 2025, 47(5): 86-93.

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  • 收稿日期:2025-01-19
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  • 在线发布日期: 2025-10-08
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