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.
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Acknowledgments
This research was supported in part by the NSF of China (Grant No.61272470, 61305087); the Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan) (Grant No. CUGL120284, CUGL120289, CUG120114).
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© 2016 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Liang, Q., Wang, G., Li, H., Zeng, D., Fan, Y., Liu, C. (2016). A Fast Vision-Based Localization Algorithm for Spacecraft in Deep Space. In: Bisio, I. (eds) Personal Satellite Services. Next-Generation Satellite Networking and Communication Systems. PSATS 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 148. Springer, Cham. https://doi.org/10.1007/978-3-319-47081-8_3
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DOI: https://doi.org/10.1007/978-3-319-47081-8_3
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