Research on the compensation in MEMS gyroscope random drift based on time-series analysis and Kalman filtering

From a practical point of view, the paper introduces an effective compensation method for MEMS gyroscope random drift. First, the MEMS data will be collected and pretreated by using time-series analysis so as to get the random drift signals. Then the ARMA model will be established and the signals will be filtered by Kalman filtering. The compensation results by Kalman filtering shows that the proposed method can effectively reduce random drift not only on the conditions but also at constant rates.