Modeling research of MEMS gyro drift Based on Kalman filter

In order to improve the performance of gyroscopes, the random drift error of a micro electro mechanical system (MEMS) gyro was analyzed and modeled. The noise feature of MEMS gyro is analyzed based on the AR model. By introducing a fading factor of Strong Tracking Filter (STF), the Sage-Husa adaptive Kalman filter reduced the effect of the error of model and noise statistical characteristics. The processed signal of a certain type of gyroscope is filtered by the new Kalman filter. Through the test on a certain type of gyroscope, the processed result from the practical simulation shows the new adaptive Kalman filter is not sensitive to the error of model and noise statistical characteristics, the accuracy of drift signal is improved greatly.