万向节
校准
惯性导航系统
加速度计
惯性测量装置
计算机科学
控制理论(社会学)
可观测性
补偿(心理学)
职位(财务)
模拟
惯性参考系
计算机视觉
物理
人工智能
数学
量子力学
操作系统
应用数学
心理学
经济
精神分析
控制(管理)
财务
作者
Pengyu Gao,Kui Li,Lei Wang,Zengjun Liu
标识
DOI:10.1088/0957-0233/27/11/115009
摘要
The navigation accuracy of the rotational inertial navigation system (RINS) could be greatly improved by periodically rotating the inertial measurement unit (IMU) with gimbals. However, error parameters in RINS should be effectively calibrated and compensated. In this paper, a self-calibration method is proposed for tri-axis RINS using attitude errors and velocity errors as measurements. The proposed calibration scheme is designed as three separate steps, and a certain gimbal rotates continuously in each step. All the error parameters in the RINS are calibrated when the whole scheme finishes. The separate calibration steps reduce the correlations between error parameters, and the observability of errors in this method is clear to demonstrate according to the relations between navigation errors and error parameters when gimbals rotate. Each calibration step only lasts 12 min, thus gyro drifts and accelerometers biases could be regarded as constant. The proposed calibration scheme is tested in both simulation and actual tri-axis RINS, and simulation and experimental results show that all 23 error parameters could be well estimated in tri-axis RINS. A long-term vehicle navigation experiment results show that after calibration and compensation, the navigation performance has doubled approximately, and the velocity accuracy is less than 2 m s−1 while the position accuracy is less than 1500 m, fully illustrating the significance of the proposed self-calibration method in improving the navigation performance of RINS.
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