Journal of Systems Engineering and Electronics ›› 2013, Vol. 35 ›› Issue (1): 152-155.doi: 10.3969/j.issn.1001-506X.2013.01.25

• 制导、导航与控制 • 上一篇    下一篇

ICDKF在SINS大方位失准角初始对准中的应用

郝燕玲1,牟宏伟1,贾鹤鸣2   

  1. 1. 哈尔滨工程大学自动化学院, 黑龙江 哈尔滨 150001;
    2. 东北林业大学机电工程学院, 黑龙江 哈尔滨 150040
  • 出版日期:2013-01-23 发布日期:2010-01-03

Application of ICDKF in initial alignment of large azimuth misalignment in SINS

HAO Yan-ling1, MU Hong-wei1, JIA He-ming2   

  1. 1. College of Automation, Harbin Engineering University, Harbin 150001, China; 2. College of Mechanical and Electrical Engineering, Northeast Forestry University, Harbin 150040, China
  • Online:2013-01-23 Published:2010-01-03

摘要:

针对大方位失准角捷联惯性导航系统误差模型非线性的特点,利用基于迭代测量更新的中心差分卡尔曼滤波(iterated central difference Kalman filter, ICDKF)方法进行初始对准。与传统的非线性扩展卡尔曼滤波相比,ICDKF不仅能够提高滤波精度,而且不需要模型的具体解析形式,避免了复杂的雅可比矩阵的推导;同时ICDKF通过迭代测量更新,提高了目前存在的中心差分卡尔曼滤波的估计精度。仿真结果进一步表明ICDKF算法的可行性与优越性,能够满足初始对准的要求。

Abstract:

In case of that the error model of strapdown inertial navigation system with large azimuth misalignment angle is nonlinear, an iterated central difference Kalman filter (ICDKF) is used in initial alignment. Compared with the traditional extended Kalman filter, ICDKF not only improves filter precision but also avoids calculating the complicated Jacobian matrix. And ICDKF can improve the estimation accuracy of existing central difference Kalman filter with iterated measurement updating procedure. The simulation results further demonstrate the feasibility and superiority of ICDKF, which the requirement of initial alignment can be met.