A novel hybrid Grey-Time Series Filtering Model of RLGs Drift Data
In order to shutdown the random drift of mechanically dithered RLGs output data effectively, a new method named Grey-Time series modeling is proposed, which has integrated the Metabolic GM(1, 1) model and Time series model. Kalman filter is used to filter the drift data based on the model which has been built, and the Allan variance is adopted to analyze the data of gyro before and after modeling and filtering. The results show that: the effect on inhibiting RLGs random drift by using this new method is better than that of traditional time series modeling and succedent Kalman filter. The method effectively decreases random error in each term of RLG, in which the improvement on quantization error is quite obvious.
RLG Grey System Time series analysis Kalman filter Allan variance
Guo Wei Jin Xun Yu Wang Xingwu Long
National University of Defense Technology College of Opo-electronic Science and Engineering Changsha China Satellite Maritime Tracking and Controlling Department Jiangyin, China
国际会议
厦门
英文
14-17
2010-10-26(万方平台首次上网日期,不代表论文的发表时间)