根据陀螺随机漂移数据的非平稳特性,建立了基于非平稳随机过程的ARIMA求和自回归滑动平均误差模型,在此模型的基础上结合卡尔曼滤波对于漂移数据进行滤波处理。实验结果表明,此方法能够有效地抑制陀螺随机误差,并且提高陀螺的精度。
According to non-stationary property of gyro random drift, this paper proposes an ARIMA model for time-series analysis, which can overcome the non-stationary random time series. After modeling, the gyro random drift is filtered by using a Kalman filter. The experimental results show that the random drift error could be effectively restrained, and the accuracy of the gym is highly improved.