Research on random drift modeling and a Kalman filter based on the differential signal of MEMS gyroscope

The Micro-Electro-Mechanical System(MEMS) gyroscope has been widely used in lots of fields such as navigation, measurement and control on account of smaller size, lower price, lighter weight and higher reliability than that of other gyroscopes. However, the large drift limits its development. From the view of practical application, a one-order autoregressive(AR) model is built for the differential signal of gyroscope based on the principle of the time series analysis and a new model which put the original signal and differential signal of gyroscope together as the state vector used in Kalman filter is proposed. The compensation results of the practical testing data of a MEMS gyroscope show that the drift error can be effectively reduced and the measurement accuracy in practice can be further improved.