Research on Time-series Modeling and Filtering Methods for MEMS Gyroscope Random Drift Error

2016 2nd International Conference on Mechanical and Aeronautical Engineering (ICMAE 2016)

机械制造;航空航天工程

Yi Wang, Xiao^1 ; Yun Meng, Xiu^1

School of Aerospace Engineering, Beijing Institute of Technology, Zhongguancun South Street, Haidian District

100081, China^1

关键词: Adaptive filtering algorithms;    Filtering method;    MEMS gyroscope;    Orthogonal property;    Random drift;    Sage-husa;    Time series modeling;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/187/1/012005/pdf
DOI  :  10.1088/1757-899X/187/1/012005

学科分类：航空航天科学

来源: IOP

【 摘 要 】

The precision of MEMS gyroscope is reduced by random drift error. This paper applied time series analysis to model random drift error of MEMS gyroscope. Based on the model established, Kalman filter was employed to compensate for the error. To overcome the disadvantages of conventional Kalman filter, Sage-Husa adaptive filtering algorithm was utilized to improve the accuracy of filtering results and the orthogonal property of innovation in the process of filtering was utilized to deal with outliers. The results showed that, compared with conventional Kalman filter, the modified filter can not only enhance filter accuracy, but also resist to outliers and this assured the stability of filtering thus improving the performance of gyroscopes.