航空学报 > 2014, Vol. 35 Issue (1): 203-214   doi: 10.7527/S1000-6893.2013.0296

一种改进的强跟踪UKF算法及其在SINS大方位失准角初始对准中的应用

郭泽, 缪玲娟, 赵洪松   

  1. 北京理工大学 自动化学院, 北京 100081
  • 收稿日期:2013-03-26 修回日期:2013-06-04 出版日期:2014-01-25 发布日期:2013-06-17
  • 通讯作者: 缪玲娟,Tel.:010-68913791 E-mail:miaolingjuan@bit.edu.cn E-mail:miaolingjuan@bit.edu.cn
  • 作者简介:郭泽 男,博士研究生。主要研究方向:捷联惯导非线性初始对准。Tel:010-68918962 E-mail:lovepeach@bit.edu.cn;缪玲娟 女,博士,教授,博士生导师。主要研究方向:惯性导航、INS/GPS组合导航、多传感器信息融合。Tel:010-68913791 E-mail:miaolingjuan@bit.edu.cn;赵洪松 男,博士研究生。主要研究方向:惯性导航、鲁棒滤波。Tel:010-68918384 E-mail:3120100354@bit.edu.cn
  • 基金资助:

    国家自然科学基金(61153002)

An Improved Strong Tracking UKF Algorithm and Its Application in SINS Initial Alignment Under Large Azimuth Misalignment Angles

GUO Ze, MIAO Lingjuan, ZHAO Hongsong   

  1. School of Automation, Beijing Institute of Technology, Beijing 100081, China
  • Received:2013-03-26 Revised:2013-06-04 Online:2014-01-25 Published:2013-06-17
  • Supported by:

    National Natural Science Foundation of China (61153002)

摘要:

针对现有的强跟踪无迹卡尔曼滤波(UKF)算法存在理论依据不足和滤波性能欠佳等问题,从正交性原理出发,通过严谨的推导得到强跟踪UKF成立的充分条件,在此基础上提出一种改进的强跟踪UKF算法。该算法无需求解雅可比矩阵且计算量较小,渐消因子的作用位置以及求解公式均不同于原始的强跟踪滤波器。给出了该算法的流程和渐消因子的求解方法,证明了该算法满足强跟踪滤波器的充分条件,并分析了其渐消因子的作用机理。进行了捷联惯性导航系统(SINS)大方位失准角初始对准仿真,结果验证了所提强跟踪UKF算法的正确性和有效性。

关键词: 大方位失准角, 初始对准, 强跟踪, 卡尔曼滤波, 无迹卡尔曼滤波, 渐消因子

Abstract:

Against the lack of theoretical basis and poor filtering performance of the existing strong tracking unscented Kalman filter (UKF) algorithms, the sufficient condition of a strong tracking UKF is rigorously derived in this paper from the orthogonality principle, based on which an improved strong tracking UKF algorithm is proposed. This new algorithm requires less computation than the existing strong tracking UKF since it does not have to calculate the Jacobian matrix, and it is different from the original strong tracking filter in both the position and solution of the fading factor. This study presents the algorithm flow and the solution to the fading factor, and proves that the improved algorithm satisfies the sufficient condition of strong tracking UKF. Furthermore, the action mechanism of the fading factor is analyzed. The results of the strapdown inertial navigation system (SINS) initial alignment simulation under large azimuth misalignment angles verify the validity and effectiveness of the improved strong tracking UKF algorithm.

Key words: large azimuth misalignment angle, initial alignment, strong tracking, Kalman filters, unscented Kalman filter, fading factor

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