基于PE-ANGO的MIMU现场标定方法

MIMU field calibration method based on PE-ANGO

针对当前微惯性测量单元(MIMU)的现场标定方法存在标定步骤复杂、不利于非专业人员操作等问题,提出了一种基于先验知识增强的自适应北苍鹰优化(PE-ANGO)算法的MIMU现场标定方法。首先分析了MIMU涉及的误差并建立了加速度计和陀螺仪的目标函数,然后使用PE-ANGO算法求解目标函数并得到最优参数。为了使得标定工作易于现场操作,引入了一种用于传感器数据采集的手持MIMU来验证所提算法。仿真结果表明:PE-ANGO算法的标定精度相较于北苍鹰优化算法提高了一个数量级。实测实验表明:标定前后对俯仰角和横滚角累积误差的抑制效果分别提高了约89%和87%;与传统标定方法相比,对俯仰角和横滚角累积误差的抑制效果分别提高了71%和68%,验证了所提方法的有效性。

Aiming at the current field calibration method of miniature inertial measurement unit(MIMU),which has the problems of complicated calibration steps and unfavourable operation for non-professionals,a field calibration method of MIMU based on the prior knowledge enhancement adaptive north goshawk optimization(PE-ANGO)algorithm is proposed.Firstly,the errors involved in MIMU are analysed and the objective functions of accelerometers and gyroscopes are established,and then the PE-ANGO algorithm is used to solve the objective functions and obtain the optimal parameters.In order to make the calibration easy to operate in the field,a handheld MIMU for sensor data acquisition is introduced to validate the proposed algorithm.Simulation results show that the calibration accuracy of the PE-ANGO algorithm is improved by one order of magnitude compared with the Northern Goshawk optimisation algorithm.The measured experiments show that before and after calibration,the suppression effect on the cumulative errors of pitch angle and roll angle is improved by 89%and 87%,respectively.Compared with the traditional calibration method,the suppression effect on the cumulative errors of pitch angle and roll angle is improved by 71%and 68%,respectively,which verifies the effectiveness of the proposed method.