中国空间科学技术

›› 2012, Vol. 32 ›› Issue (3): 7-14.doi: 10.3780/j.issn.1000-758X.2012.03.002

• 研究探讨 • 上一篇    下一篇

基于IMM-UKF的航天器相对位姿确定算法

 岳晓奎, 李彬, 赵凯   

  1. (西北工业大学航天学院，西安 710072)
  • 收稿日期:2011-04-21 修回日期:2012-06-25 出版日期:2012-06-25 发布日期:2012-06-25
  • 作者简介:岳晓奎 1970年生，2002年获西北工业大学飞行器设计专业博士学位，教授，博士生导师。研究方向为航天器动力学与控制、视觉相对导航。
  • 基金资助:

    国家自然科学基金（11172235），高等学校博士学科点专项科研基金（20106102110003）资助项目

Vision-based IMM-UKF Spacecraft Relative Position and Attitude Determination Algorithm

 YUE  Xiao-Kui, LI  Bin, ZHAO  Kai   

  1. (College of Astronautics，Northwestern Polytechnical University，Xi′an 710072)
  • Received:2011-04-21 Revised:2012-06-25 Published:2012-06-25 Online:2012-06-25

PDF (PC)

1830

被引次数

4

摘要： 在航天器相对导航过程中，相对距离测量信息容易受到干扰，测量误差有较大的不确定性，通常基于单一模型的滤波算法无法对噪声进行辨识，很难获得精确的导航结果。针对应用Clohessy-Wiltshire (C-W)方程受到圆轨道假设的限制问题，研究了建立在惯性坐标系下的近距离相对运动方程(Lawden方程)，建立了基于这两个方程的模型集。根据导航系统测量敏感器的特点，设计基于Rodrigues参数及无迹卡尔曼滤波(UKF)的交互式多模型(IMM)视觉相对位姿动态估计算法(IMM-UKF)，在保证计算效率的前提下，确保相对轨道姿态确定的稳定性和精确性。数值仿真验证了算法的有效性和先进性。

关键词: 相对位姿, 视觉导航, 交互式多模型, 无迹卡尔曼滤波, 航天器

Abstract: In the  process of spacecraft relative navigation, the relative distance measurement information is susceptible to disturbances, which results in greatuncertainty of measurement error. In general, filtering algorithm based on a single model cannot identify the noise and it is difficult to obtain accurate navigation results. As for the limitation of circle orbit  assumption, close relative motion equation (Lawden equation) was studied in the inertial coordinate system using Clohessy-Wiltshire (C-W) equation, and the two equations were established based on the model set. Considering the characteristics of the navigation sensors, a vision based dynamical algorithm of relative position and attitudes estimation using interacting multiple model (IMM-UKF) algorithm was designed based on the Rodrigues parameters and UKF filtering algorithm. The stability and precision of the relative orbit and attitudes determination are certified by using this algorithm under the condition of computation efficiency guarantee.

Key words: Relative position and attitudes, Vision-based navigation, Interacting multiple model, Unscented Kalman filter, Spacecraft