北京航空航天大学学报 ›› 2018, Vol. 44 ›› Issue (1): 1-9.doi: 10.13700/j.bh.1001-5965.2017.0021

• 论文 • 上一篇    下一篇

地标自主导航的高精度地标库建立方法

杨博, 张典律, 赵晓涛   

  1. 北京航空航天大学 宇航学院, 北京 100083
  • 收稿日期:2017-01-16 修回日期:2017-04-24 出版日期:2018-01-20 发布日期:2017-06-27
  • 通讯作者: 杨博 E-mail:yangbo@buaa.edu.cn
  • 作者简介:杨博,女,博士,副教授。主要研究方向:航天器天文自主导航技术;张典律,男,硕士研究生。主要研究方向:导航制导与控制;赵晓涛,男,硕士研究生。主要研究方向:导航制导与控制。

A building method of high-precision landmark library for landmark autonomous navigation

YANG Bo, ZHANG Dianlyu, ZHAO Xiaotao   

  1. School of Astronautics, Beijing University of Aeronautics and Astronautics, Beijing 100083, China
  • Received:2017-01-16 Revised:2017-04-24 Online:2018-01-20 Published:2017-06-27

摘要: 利用地标信息的卫星自主导航方法是通过星载光学摄像机实时拍摄地标景象来计算卫星的位置、速度等参数,具有完全自主的特点,并且适用范围广泛,可用于能够周期性获得地面图像的航天器,但受到地标选取方法以及地标库建立策略的制约,影响到导航精度,阻碍了推广使用。针对上述问题,提出了建立全局及高性能的地标库,即采用全球地标控制点选取的原则选取性能优良的全球地标样本,并自动生成全局地标库。通过计算机仿真验证了该方法的有效性,结果表明,使用全球地标控制点选取地标样本,并自动生成全局地标库,可以快速而准确地为航天器进行高精度的自主导航,导航位置误差约为99 m,速度误差约为0.08 m/s。

关键词: 卫星自主导航, 地标导航, 地标库, 灰度场特征参数, 最大相关系数(MCC)法

Abstract: Satellite autonomous navigation based on landmark information can be used for all kinds of satellites which can periodically obtain images of earth surface for its high accuracy and independence. This method has been restricted by landmark selection method and the establishment strategy of landmark library, which affect the navigation precision and hinder the popularization and application of this navigation method. To solve these problems, a method for establishing global high-performance landmark library is proposed. The global landmark library could be automatically generated by using global landmark control areas to select high-quality global landmark samples. To verify the feasibility of the proposed method, a simulation program was designed. The results show that the position error of the landmark navigation system based on the new landmark library is about 99 m, and velocity error is about 0.08 m/s. The proposed method can provide high-precision autonomous navigation for spacecraft fast and accurately.

Key words: satellite autonomous navigation, landmark navigation, landmark library, grayscale field characteristic parameter, maximum correlation coefficient (MCC) algorithm

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