title: FOG Random Drift Signal Denoising Based on the Improved AR Model and Modified Sage-Husa Adaptive Kalman Filter.
abstract: In order to reduce the influence of fiber optic gyroscope (FOG) random drift error on inertial navigation systems, an improved auto regressive (AR) model is put forward in this paper. First, based on real-time observations at each restart of the gyroscope, the model of FOG random drift can be established online. In the improved AR model, the FOG measured signal is employed instead of the zero mean signals. Then, the modified Sage-Husa adaptive Kalman filter (SHAKF) is introduced, which can directly carry out real-time filtering on the FOG signals. Finally, static and dynamic experiments are done to verify the effectiveness. The filtering results are analyzed with Allan variance. The analysis results show that the improved AR model has high fitting accuracy and strong adaptability, and the minimum fitting accuracy of single noise is 93.2%. Based on the improved AR(3) model, the denoising method of SHAKF is more effective than traditional methods, and its effect is better than 30%. The random drift error of FOG is reduced effectively, and the precision of the FOG is improved.
authors.affiliation: Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology, Ministry of Education, School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China. sunjin8607986@126.com.
authors.forename: Jin
authors.initials: J
authors.lastname: Sun
authors.affiliation: Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology, Ministry of Education, School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China. xxs@seu.edu.cn.
authors.forename: Xiaosu
authors.initials: X
authors.lastname: Xu
authors.affiliation: Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology, Ministry of Education, School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China. gcdlyt1985@163.com.
authors.forename: Yiting
authors.initials: Y
authors.lastname: Liu
authors.affiliation: Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology, Ministry of Education, School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China. ztandyy@163.com.
authors.forename: Tao
authors.initials: T
authors.lastname: Zhang
authors.affiliation: Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology, Ministry of Education, School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China. lyjenny11@163.com.
authors.forename: Yao
authors.initials: Y
authors.lastname: Li
keywords: Sage-Husa adaptive Kalman filter (SHAKF); auto regressive (AR) model; fiber optic gyroscope (FOG); online model; random drift