Wang Zihui, Cheng Xianghong, Fu Jinbo
School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China.
Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology, Ministry of Education, Southeast University, Nanjing 210096, China.
Sensors (Basel). 2019 Aug 15;19(16):3568. doi: 10.3390/s19163568.
Navigation grade inertial measurement units (IMUs) should be calibrated after Inertial Navigation Systems (INSs) are assembled and be re-calibrated after certain periods of time. The multi-position calibration methods with advantage of not requiring high-precision equipment are widely discussed. However, the existing multi-position calibration methods for IMU are based on the model of linear scale factors. To improve the precision of INS, the nonlinear scale factors should be calibrated accurately. This paper proposes an optimized multi-position calibration method with nonlinear scale factor for IMU, and the optimal calibration motion of IMU has been designed based on the analysis of sensitivity of the cost function to the calibration parameters. Besides, in order to improve the accuracy and robustness of the optimization, an estimation method on initial values is presented to solve the problem of setting initial values for iterative methods. Simulations and experiments show that the proposed method outperforms the calibration method without nonlinear scale factors. The navigation accuracy of INS can be improved by up to 17% in lab conditions and 12% in the moving vehicle experiment, respectively.
导航级惯性测量单元（IMU）应在惯性导航系统（INS）组装后进行校准，并在经过一定时间后重新校准。具有无需高精度设备优势的多位置校准方法得到了广泛讨论。然而，现有的IMU多位置校准方法是基于线性比例因子模型。为提高INS的精度，应准确校准非线性比例因子。本文提出了一种针对IMU的具有非线性比例因子的优化多位置校准方法，并在分析成本函数对校准参数的灵敏度的基础上设计了IMU的最优校准运动。此外，为提高优化的准确性和鲁棒性，提出了一种初始值估计方法来解决迭代方法的初始值设置问题。仿真和实验表明，所提出的方法优于没有非线性比例因子的校准方法。在实验室条件下，INS的导航精度可分别提高高达17%，在移动车辆实验中可提高12%。
