Modeling Research of MEMS Gyro Drift Based on Kalman Filter

摘要：

　　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.

关键词： Drift error MEMS Fading factor Adaptive Kalman Filtering

作者: RUAN Xiao-gang YU Miao-miao

作者单位: College of Electronic Information and Control Engineering,Beijing University of Technology,Beijing,100124,China

会议类型: 国际会议

会议名称: 第26届中国控制与决策会议(2014 CCDC)

会议地点: 长沙

会议语种:英文

页码: 2949-2952

在线出版日期: 2014-05-31（万方平台首次上网日期，不代表论文的发表时间）