Personal Satellite Services. Next-Generation Satellite Networking and Communication Systems. 6th International Conference, PSATS 2014, Genoa, Italy, July 28–29, 2014, Revised Selected Papers

Research Article

A Fast Vision-Based Localization Algorithm for Spacecraft in Deep Space

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  • @INPROCEEDINGS{10.1007/978-3-319-47081-8_3,
        author={Qingzhong Liang and Guangjun Wang and Hui Li and Deze Zeng and Yuanyuan Fan and Chao Liu},
        title={A Fast Vision-Based Localization Algorithm for Spacecraft in Deep Space},
        proceedings={Personal Satellite Services. Next-Generation Satellite Networking and Communication Systems. 6th International Conference, PSATS 2014, Genoa, Italy, July 28--29, 2014, Revised Selected Papers},
        proceedings_a={PSATS},
        year={2017},
        month={1},
        keywords={Smearing image Autonomous navigation Star extraction},
        doi={10.1007/978-3-319-47081-8_3}
    }
    
  • Qingzhong Liang
    Guangjun Wang
    Hui Li
    Deze Zeng
    Yuanyuan Fan
    Chao Liu
    Year: 2017
    A Fast Vision-Based Localization Algorithm for Spacecraft in Deep Space
    PSATS
    Springer
    DOI: 10.1007/978-3-319-47081-8_3
Qingzhong Liang1,*, Guangjun Wang1,*, Hui Li1,*, Deze Zeng1,*, Yuanyuan Fan1,*, Chao Liu1,*
  • 1: China University of Geosciences
*Contact email: qzliang@cug.edu.cn, gjwang@cug.edu.cn, lihuicug@cug.edu.cn, dzzeng@cug.edu.cn, yyfan@cug.edu.cn, liuchao@cug.edu.cn

Abstract

Star light navigation can provide the current attitude and position of the spacecraft in deep space. However, the accuracy of stellar-inertial attitude determination is degraded because of star image smearing under high dynamic condition. To solve this problem, two key work, including accuracy star extraction and fast star identification, should be done. In this paper, we bring interpolation algorithm into contiguous area pixel searching for star extraction, and get sub-pixel coordinate information of the star points. In addition, a divisional method is proposed to improve star identification algorithm speed based on Hausdorff distance. The simulation results show that work not only has accuracy identification rate but also has better recognition speed. It was used successfully in the actual projects.