Based on Kalman filter processing of FOG signal

Yuhang Xuebao/Journal of Astronautics

Volumn 30, Issue 2, 2009, Pages 604-608

  Liu, Jian Feng ^a   Jiang, Yong ^a   Ding, Chuan Hong ^a  

^a CHINA AEROSPACE SCIENCE AND INDUSTRY CORPORATION   (China)

Author keywords

ARMA; FOG; Kalman filtering; Random model; Time series

Indexed keywords

AUTOREGRESSIVE MOVING AVERAGE; ESTIMATING PARAMETERS; FIBER OPTIC GYRO; FORECAST METHOD; KALMAN-FILTERING; POWER SPECTRUM DENSITY; RANDOM DRIFT; RANDOM MODEL; TIME SERIES FORECASTING;

ELECTRIC LOAD FORECASTING; FIBER OPTICS; FOG; TIME SERIES;

KALMAN FILTERS;

EID: 70249095558     PISSN: 10001328     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (8)

1. Yang Shu-Zi, Wu Ya. Time series analysis of the engineering application: on the list[M]. Wuhan: Huazhong University of Science Press, 1996.
2. Guo Xiu-Zhong. INS Gyroscope Theory[M]. Beijing: National Defense Industry Press, 1996.
3. Zhang Shu-Xia, Wu Jian-Tong. Data Modeling and Forecasting[M]. Harbin: Harbin Engineering University Press, 1999.
4. Pandit S M, Wu S M. Time Series and System Analysis with Application. John wiloy and sons,1983.Forecasting[J]. Applied Artifical Intelligence, 2001, 12(2): 105-127.
5. Figueiredo M. Adaptive Sparseness for supervised learning[J]. IEEE Trans on Pattern Analysis and Machine Intelligence, 2003, 25(9): 1150-1159.
6. Zhu Kui-Bao, Zhang Chun-Xi, Zhang Xiao-Yue. Research of FOG random drift ARMA model[J]. Journal of Astronautics, 2006, 27(5): 1118-1121 (in Chinese).
7. Qin Yong-Yuan, Zhang Hong-Yue, Wang Shu-Hua. Kalman Filter with Integrated Navigation Principles[M]. Xi'an: Northwestern University Press, 1998.
8. Pepper D M, Wang HTM. Nuclear Magnetic Resonance Gyroscopes: AD-A124925, 2004.