Research on vibration error suppression of MEMS gyroscope based on improved adaptive filtering
A compensation algorithm for random vibration error of MEMS gyroscope based on improved adaptive filtering is proposed.The algorithm uses a simplified Sage-Husa adaptive filtering algorithm to estimate measurement noise and convergence criterion is introduced to suppress filtering divergence by the covariance matching technique,which improves the real-time performance and reduces the computation quantity.The experimental results show that the variance of random vibration error of MEMS gyroscope is reduced by 97.76％after the algorithm filtering is improved,and the variance of the improved algorithm is reduced by 72.66％,compared with the conventional Kalman filtering.It is verified that the improved adaptive Kalman filtering algorithm can effectively suppress the output error caused by the random vibration of the MEMS gyroscope.
MEMS gyroscopesimplified Sage-Husa adaptive filteringtime-series model
万方数据
维普
