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动态干扰条件下的旋转式捷联惯导系统自对准方法

DOI: 10.3724/SP.J.1004.2014.02050, PP. 2050-2056

Keywords: 旋转式捷联惯导系统,初始对准,惯性系,自适应滤波,多渐消因子

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Abstract:

?针对角晃动与线晃动等动态干扰条件下,旋转式捷联惯导系统(Rotarystrapdowninertialnavigationsystem,RotarySINS)难以实现自对准的问题,提出了一种基于惯性系的自对准新算法.首先,基于惯性系下粗对准的结果,推导了双轴转动调制捷联惯导系统的惯性系精对准误差模型;然后,针对观测模型的噪声不确定性问题,通过改变渐消因子阵的嵌入方式,提出了一种改进的多渐消因子自适应Kalman滤波方法.最后,仿真实验证明该方法能够有效解决动态干扰条件下旋转式捷联惯导系统的自对准问题,实现快速自主高精度对准.

References

[1]  Sun Feng, Sun Wei. Coarse alignment of SINS based on IMU single-axial rotation. Systems Engineering and Electronics, 2010, 32(6): 1272-1276(孙枫, 孙伟. 基于单轴转动的捷联系统粗对准技术研究. 系统工程与电子技术, 2010, 32(6): 1272-1276)
[2]  Xia Qi-Jun, Sun You-Xian, Zhou Chun-Hui. An optimal adaptive algorithm for fading Kalman filter and its application. Acta Automatica Sinica, 199016(3): 210-216(夏启军, 孙优贤, 周春晖. 渐消卡尔曼滤波器的最佳自适应算法及其应用. 自动化学报, 1990, 16(3): 210-216)
[3]  Zhou Dong-Hua, Xi Yu-Geng, Zhang Zhong-Jun. A suboptimal multiple fading extended Kalman filter. Acta Automatica Sinica, 1991, 17(6): 689-695, 758(周东华, 席裕庚, 张钟俊. 一种带多重次优渐消因子的扩展卡尔曼滤波器. 自动化学报, 1991, 17(6): 689-695, 758)
[4]  Shi Yong, Han Chong-Zhao. Adaptive UKF method with applications to target tracking. Acta Automatica Sinica, 2011, 37(6): 755-759(石勇, 韩崇昭. 自适应UKF算法在目标跟踪中的应用. 自动化学报, 2011, 37(6): 755-759)
[5]  Weng Hai-Na, Lu Quan-Cong, Huang Kun, Zhang Yu-Fei, Yang Gong-Liu. Rotation scheme design for rotary optical gyro SINS. Journal of Chinese Inertial Technology, 2009, 17(1): 8-14(翁海娜, 陆全聪, 黄昆, 张宇飞, 杨功流. 旋转式光学陀螺捷联惯导系统的旋转方案设计. 中国惯性技术学报, 2009, 17(1): 8-14)
[6]  Qin Yong-Yuan, Yan Gong-Min, Gu Dong-Qing, Zheng Ji-Bing. A clever way of SINS coarse alignment despite rocking ship. Journal of Northwestern Polytechnical University, 2005, 23(5): 681-684(秦永元, 严恭敏, 顾冬晴, 郑吉兵. 摇摆基座上基于信息的捷联惯导粗对准研究. 西北工业大学学报, 2005, 23(5): 681-684)
[7]  Sun Feng, Cao Tong. Accuracy analysis of coarse alignment based on gravity in inertial frame. Chinese Journal of Scientific Instrument, 2011, 32(11): 2409-2415(孙枫, 曹通. 基于重力信息的惯性系粗对准精度分析. 仪器仪表学报, 2011, 32(11): 2409-2415)
[8]  Gu D Q, Naser El-Sheimy, Hassan T, Syed Z. Coarse alignment for marine SINS using gravity in the inertial frame as a reference. In: Proceedings of the IEEE/ION Position, Location and Navigation Symposium, Monterey, CA. Monterey, CA: IEEE, 2008. 961-965
[9]  Najjaran H, Goldenberg A. Real-time motion planning of an autonomous mobile manipulator using a fuzzy adaptive Kalman filter. Robotics and Autonomous Systems, 2006, 55(2): 96-106
[10]  J. Ali. Strapdown inertial navigation system/astronavigation system data synthesis using innovation-based fuzzy adaptive Kalman filtering. IET Science, Measurement and Technology, 2010, 4(5): 246-255
[11]  Wang Xiang-Hua, Qin Zheng, Yang Xin-Yu, Yang Hui-Jie. Adaptive algorithm for adjusting observation noises based on double-Kalman filter. Systems Engineering and Electronics, 2010, 32(2): 232-234(王向华, 覃征, 杨新宇, 杨慧杰. 基于两次Kalman滤波的观测噪声自适应调整算法. 系统工程与电子技术, 2010, 32(2): 232-234)
[12]  Yu M J. INS/GPS integration system using adaptive filter for estimating measurement noise variance. IEEE Transactions on Aerospace and Electronic Systems, 2012, 48(2): 1786-1792
[13]  Qian Hua-Ming, Ge Lei, Peng Yu. Multiple fading factors Kalman filter and its application in SINS initial alignment. Journal of Chinese Inertial Technology, 2012, 20(3): 287-291(钱华明, 葛磊, 彭宇. 多渐消因子卡尔曼滤波及其在SINS初始对准中的应用. 中国惯性技术学报, 2012, 20(3): 287-291)
[14]  Gao W X, Miao L J, Ni M L. Multiple fading factors Kalman filter for SINS static alignment application. Chinese Journal of Aeronautics, 2011, 24(4): 476-483
[15]  Gao W, Ben Y Y, Zhang X, Li Q, Yu F. Rapid fine Strapdown INS alignment method under marine mooring condition. IEEE Transactions on Aerospace and Electronic Systems, 2011, 47(4): 2887-2896

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