Title :
Research on random drift modeling and a Kalman filter based on the differential signal of MEMS gyroscope
Author :
Xia Yan ; Chen Wenjie ; Peng Wenhui
Author_Institution :
Sch. of Autom., Beijing Inst. of Technol., Beijing, China
Abstract :
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.
Keywords :
Kalman filters; autoregressive processes; gyroscopes; micromechanical devices; random processes; time series; AR model; Kalman filter; MEMS gyroscope testing data; differential signal; microelectromechanical system gyroscope; one-order autoregressive model; random drift modeling; state vector; time series analysis; Analytical models; Equations; Gyroscopes; Kalman filters; Mathematical model; Micromechanical devices; Time series analysis; AR; Kalman filter; MEMS gyroscope; differential signal;
Conference_Titel :
Control and Decision Conference (CCDC), 2013 25th Chinese
Conference_Location :
Guiyang
Print_ISBN :
978-1-4673-5533-9
DOI :
10.1109/CCDC.2013.6561504
