宇航学报 ›› 2018, Vol. 39 ›› Issue (11): 1228-1237.doi: 10.3873/j.issn.1000-1328.2018.11.005

• 制导、导航、控制与电子 • 上一篇    下一篇

星间相对测量自主导航的改进容积卡尔曼滤波

张艾,李勇   

  1. 中国空间技术研究院钱学森空间技术实验室,北京 100094
  • 收稿日期:2017-12-25 修回日期:2018-04-18 出版日期:2018-11-15 发布日期:2018-11-25
  • 基金资助:

    国家重点基础研究发展计划(2014CB845303)

A Modified Cubature Kalman Filter for Autonomous Navigation Based on Relative Measurements Between Satellites

ZHANG Ai, LI Yong   

  1. Qian Xuesen Laboratory of Space Technology, China Academy of Space Technology, Beijing 100094, China
  • Received:2017-12-25 Revised:2018-04-18 Online:2018-11-15 Published:2018-11-25

摘要:

针对仅利用星间相对位置测量的双星自主导航系统,提出一种基于可观度的改进容积卡尔曼滤波算法。该算法从系统可观度的物理意义出发,通过对预测协方差阵进行在线调整改善标准容积卡尔曼滤波算法对系统可观度敏感和不满足滤波拟一致性等问题。对具体算例进行数值仿真,校验了该改进容积卡尔曼滤波算法在基于星间相对位置测量的双星自主导航系统中的有效性,与标准容积卡尔曼滤波相比趋稳更快,精度更高。

关键词: 自主导航, 容积卡尔曼滤波(CKF), 可观性分析

Abstract:

 In this paper, a modified quasi-consistent cubature Kalman filter (MCKF) based on relative position measurements in a dual-satellite system is proposed for the autonomous navigation of a distributed satellite system (DSS). The only difference between the MCKF and the standard cubature Kalman filter (CKF) is that in MCKF the error covariance matrix from the observability theory of a nonlinear system is adjusted on line. The numerical simulations show that the MCKF is quasi-consistent and less sensitive to the observable degree than the usual one. Moreover, it indicats that the MCKF can shorten the stabilizing time of the systems with high accuracy.

Key words:  Autonomous navigation, Cubature Kalman filter (CKF), Observability analysis

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