MEMS陀螺静态误差补偿方法研究

Research on Static Error Compensation Method of MEMS Gyroscope

针对典型MEMS陀螺静态误差大、影响工程上使用的难题,提出基于时间序列模型的Kalman滤波方法。通过对典型MEMS陀螺数据进行分析,提取其趋势项,进行周期检验与相关性分析,建立时间序列模型;针对建立的时间序列模型,提出利用Kalman滤波方法,消除零位不稳定性。仿真及试验结果表明,该解算方法能够有效补偿MEMS陀螺静态误差,显著提升其静态指标。

In view of the large static error of typical MEMS gyroscope and the difficult problem in engineering, a Kalman filtering method based on time series model is proposed. Based on the typical MEMS gyro data analysis, extraction of the trend analysis, periodic inspection and correlation, time series model is established. According to the time sequence model, proposed using Kalman filtering method to eliminate the zero stability. Simulation and experimental results show that the proposed method can effectively compensate the static error of MEMS gyro and improve its static index significantly.