Temperature compensation for fiber optic gyroscope based on dual models

被引:0
作者
School of Instrumentation Science & Opto-electronics Engineering, Beihang University, Beijing [1 ]
100191, China
不详 [2 ]
100191, China
不详 [3 ]
100192, China
机构
[1] School of Instrumentation Science & Opto-electronics Engineering, Beihang University, Beijing
[2] Science and Technology on Inertial Laboratory, Beihang University, Beijing
[3] China Ship Research and Development Academy, Beijing
来源
Zhongguo Guanxing Jishu Xuebao | / 1卷 / 131-136期
关键词
Fiber optic gyroscope; Kalman filtering; Polynomial model; Temperature drift;
D O I
10.13695/j.cnki.12-1222/o3.2015.01.27
中图分类号
学科分类号
摘要
In FOG-based strapdown inertial navigation system (SINS), the temperature variation's influence on zero bias of FOG is one of the key factors that degrades the performance, which consists of two parts: a deterministic part and a random part. In this paper, a polynomial model based on correlation analysis is proposed to compensate the deterministic effect of temperature on FOG bias output, and the remaining drift of FOG is compensated based on Kalman filter (KF) model combined with time series analysis to reduce the random drift. This novel dual temperature modeling and compensation method for FOG is established respectively according to the different characteristics of the deterministic and random parts. Traditional single polynomial model is also investigated to provide a comparison with the proposed approach. Experimental results show that the bias stability of FOG output is increased to 0.01 (°)/h from 0.05 (°)/h after compensation by this novel method, while it is increased only to 0.04 (°)/h from 0.05 (°)/h by the traditional single polynomial model. The new method is shown to be more effective in compensating FOG temperature drift and improving FOG accuracy and has significant practical values in engineering. ©, 2015, Editorial Department of Journal of Chinese Inertial Technology. All right reserved.
引用
收藏
页码:131 / 136
页数:5
相关论文
共 16 条
[1]  
Kurbatov A.M., Kurbatov R.A., Temperature characteristics of fiber-optic gyroscope sensing coils, Journal of Communications Technology and Electronics, 58, 7, pp. 745-752, (2013)
[2]  
Zhang Y.G., Gao Z.X., Wang G.C., Et al., Modeling of thermal-induced rate error for FOG with temperature ranging from -40℃ to 60℃, IEEE Photonics Technology Letters, 26, 1, pp. 18-21, (2014)
[3]  
Narasimhappa M., Sabat S.L., Peessapati R., Nayak J., An innovation based random weighting estimation mechanism for denoising fibe optic gyro drift signal, Optik, 125, pp. 1192-1198, (2014)
[4]  
Jin J., Wang Z., Zhang Z.G., Et al., Errors modeling for fiber optic gyroscope using multiple linear regression models, Journal of Astronautics, 29, 6, pp. 1912-1916, (2008)
[5]  
Liu Y.Y., Yang G.L., Li S.Y., Application of BP-Bagging model in temperature compensation for fiber optic gyro-scope, Journal of Chinese Inertial Technology, 22, 2, pp. 254-259, (2014)
[6]  
Chen X.Y., Shen C., Study on temperature error processing technique for fiber optic gyroscope, Optik, 124, pp. 784-792, (2013)
[7]  
Liu Y.Y., Yang G.L., Li S.Y., Application of BP-AdaBoost model in temperature compensation for fiber optic gyroscope bias, Journal of Beijing University of Aeronautics and Astronautics, 40, 2, pp. 235-239, (2014)
[8]  
Cheng J.C., Fang J.C., Wu W.R., Et al., Temperature drift modeling and compensation of RLG based on PSO turning SVM, Measurement, 55, pp. 246-254, (2014)
[9]  
Wei G., Li G., Wu Y., Et al., Application of Least Squares Support Vector Machine in system-level temperature compensation of ring laser gyroscope, Measurement, 44, pp. 1898-1903, (2011)
[10]  
Wu X.M., Li D., Chen W.H., A Kalman filter approach based on random drift data of fiber optic gyro, IEEE Conference on Industrial Electronics and Applications, pp. 1933-1937, (2011)