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Star Map Processing Algorithm of Star Sensor and Autonomous Celestial Navigation

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INS/CNS/GNSS Integrated Navigation Technology

Abstract

Celestial navigation is a kind of fully autonomous navigation method. It has the following characteristics: (1) no additional equipment, except the standard attitude sensors such as star sensor and earth sensor, is needed; (2) both orbit information and attitude data can be provided; and (3) self-contained, nonradiating. So, it has broad application in satellites, airships, deep space explorers, etc. The method is based on information about a celestial body (Sun, Earth, Moon, and stars) in an inertial frame at a certain time. With the increasing development of autonomous celestial navigation technology, the method of using celestial sensors to determinate spacecraft attitude has been widely studied. Currently, star sensors are widely used to realize high-precision spacecraft navigation. In this chapter, the star map preprocessing method of star sensor is studied first, which includes the processing method for fuzzy star maps and distortion correction method for star maps, providing high-quality star maps for star map matching. Second, an effective star map identification method is introduced to acquire effective starlight vector direction. Finally, a star sensor-based celestial navigation method is proposed.

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Authors and Affiliations

  1. Beijing University of Aeronautics and Astronautics, Beijing, China

    Wei Quan, Xiaolin Gong, Jiancheng Fang & Jianli Li

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  1. Wei Quan
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  2. Xiaolin Gong
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  3. Jiancheng Fang
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  4. Jianli Li
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Correspondence to Wei Quan .

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© 2015 National Defense Industry Press, Beijing and Springer-Verlag Berlin Heidelberg

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Quan, W., Gong, X., Fang, J., Li, J. (2015). Star Map Processing Algorithm of Star Sensor and Autonomous Celestial Navigation. In: INS/CNS/GNSS Integrated Navigation Technology. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45159-5_5

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  • DOI: https://doi.org/10.1007/978-3-662-45159-5_5

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  • Print ISBN: 978-3-662-45158-8

  • Online ISBN: 978-3-662-45159-5

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