Real-time filtering methods of FOG random noise based on ARMA model

被引：0

作者：

Navigation Research Center, Nanjing University of Aeronautics and Astronautics, Nanjing ^{[1
]}

210016, China

不详 ^{[2
]}

210037, China

不详 ^{[3
]}

721006, China

机构：

[1] Navigation Research Center, Nanjing University of Aeronautics and Astronautics, Nanjing

[2] Automation Department, Nanjing Forestry University, Nanjing

[3] Shaanxi Baocheng Aviation Instrument Co., Ltd., Aviation Industry Corporation of China, Baoji

来源：

Zhongguo Guanxing Jishu Xuebao | / 1卷 / 120-124期

关键词：

Adaptive Kalman filtering; ARMA; Gyroscope random noise; Time series analysis;

D O I：

10.13695/j.cnki.12-1222/o3.2015.01.25

中图分类号：

学科分类号：

摘要：

The modeling and filtering methods of FOG random noise based on ARMA (Auto-Regressive and Moving Average) model are studied. A new method for whitening colored system noise is presented to solve the problem that colored system noise can not be whitened by traditional state-expand methods: The parameters as well as the white noise of ARMA model are estimated by extended least squares (ELS) algorithm; Then the colored system noise can be whitened by being expanded to system equation as control input term; By Sage-Husa's maximum a posteriori(MAP) noise estimator, the estimated mean and variance of the system noise are achieved; Finally an adaptive Kalman filter is employed to eliminate the error and achieve accurate state estimation. Test results indicate that, for the FOG which output noise has trailing characteristics on both self-correlation and partial correlation, the noise reduction effect based on the new filtering method is improved by >10% compared with that of traditional AR model-based methods. ©, 2015, Editorial Department of Journal of Chinese Inertial Technology. All right reserved.

引用

页码：120 / 124

页数：4

共 13 条

[1] Guo L., Wu X.-Z., Jin Y., Building model of the drift of the fiber optic gyroscope and application in the error equation of inertial navigation system, Optical Technique, 39, 4, pp. 328-330, (2013)
[2] Liu X.-G., Hu J.-T., Bai X.-P., Et al., Random error analysis and modeling for micromechanical gyro of transplanter, Journal of Chinese Inertial Technology, 21, 2, pp. 250-254, (2013)
[3] Darry B., Lee S., Norman T., Et al., Method and apparatus for monitoring angle random walk of fiber optic gyroscope
[4] Han S., Wang J., Quantization and colored noises error modeling for inertial sensors for GPS/INS integration, IEEE Sensors Journal, 11, 6, pp. 1493-1503, (2011)
[5] Li J.-L., Xu H.-L., He J., Real-time filtering methods of random drift of fiber optic gyroscope, Journal of Astronautics, 31, 12, pp. 2717-2721, (2010)
[6] Li Y., Hu B.-Q., Qin F.-J., Li K., Online estimation of ARW coefficient of fiber optic gyro, Mathematical Problems in Engineering, 2014, pp. 1-10, (2014)
[7] Georgy J., Noureldin A., Korenberg M.J., Et al., Modeling the stochastic drift of a MEMS-based gyroscope in gyro/odometer/GPS integrated navigation, Intelligent Transportation Systems, 11, 4, pp. 856-872, (2010)
[8] Kim D., M'Closkey R.T., Spectral analysis of vibratory gyro noise, Sensors Journal, 13, 11, pp. 4361-4374, (2013)
[9] Zheng Z.-M., Liu J.-Y., Lai J.-Z., Et al., Filtering technique on FOG random noise and its application, Journal of Data Acquisition & Processing, 24, 5, pp. 671-675, (2009)
[10] Xing Z.Q., Demoz G.E., Modeling and bounding low cost inertial sensor errors, IEEE/ION Position, Location and Navigation Symposium, pp. 1222-1232, (2012)

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