中国空间科学技术

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基于多传感器的卫星自主导航信息融合算法

李丹;刘建业;熊智;张丽敏;   

  1. 南京航空航天大学导航研究中心;
  • 发布日期:2008-08-25

Information Fusion Algorithm of Satellite Multi-sensor Autonomous Navigation System

Li Dan Liu Jianye Xiong Zhi Zhang Limin (Navigation Research Center,Nanjing University of Aeronautics and Astronautics,Nanjing 210016)   

  • Online:2008-08-25
  • Supported by:
    863资助项目(项目编号2006AA704312)

被引次数

2

摘要： 通常卫星上装有较多的自主导航传感器,如何将其信息有效的组织并充分利用,是卫星自主导航的关键问题。采用信息融合技术把两种或多种导航系统组合起来,应用最优估计理论,形成最优组合导航系统,有利于充分运用各导航系统的信息进行信息互补和信息合作,已逐渐成为了导航定位技术的发展方向。文章针对星敏感器、红外地平仪、雷达高度计、紫外敏感器组成的卫星自主导航系统的特点,提出了一种基于联邦卡尔曼滤波技术进行轨道确定的信息融合算法。仿真结果表明,该方案能够获得较高的定轨精度,有效抑制滤波发散,整个系统的运算速度和收敛速度也有所提高。

关键词: 组合导航, 信息融合, 卡尔曼滤波, 卫星

Abstract: There are many navigation sensors onboard a satellite.The main question is how to manage and use the information they supplied.Combining two or more navigation systems with information fusion technology and optimal estimation theory becomes the trend of the navigation techniques.It takes full advantage of the system complementarily.A satellite autonomous orbit determination system which composed of star tracker,infrared horizon sensor,radar altimeter and ultraviolet sensor was put forword.Base on that system,a federated kalman filter and a new information fusion algorithm were presented.The simulation results verify that this method can obtain high accuracy and reliability.The divergence of filter can be controlled.The calculation speed and convergence speed to the whole system also can be improved.

Key words: Combined navigation, Information fusion, Kalman filter, Satellite