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Proceedings Paper

Three-dimensional grid algorithm for all-sky autonomous star identification
Author(s): Wen-jun Yi; Hai-bo Liu; Jian-kun Yang; Hui Jia; Li-xin Yang
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Paper Abstract

Grid algorithm is a classical star identification algorithm based on star pattern. A three-dimensional grid algorithm for all-sky autonomous star identification is proposed, which is associated with the information of star view magnitude. In contrast with traditional grid algorithm that constructs the grid cells on two-dimensional plane (e.g. x-y coordinate plane), the proposed approach makes use of the star view magnitudes of the neighboring stars as the third dimension (e.g. z-axis). A pattern is generated for each of its three-dimensional grid cells that contain neighboring star are 1, and those without are 0. The progress of star identification is to determine which pattern in the database is associated with the particular sensor pattern. Simulation shows that this method can achieve identification rate of 98.0% while the standard deviation of star position error and star view magnitudes are 1 pixel and 0.3Mv respectively. Compared with the traditional grid algorithm, the identification rate is higher, and the average runtime is 50 percent shorter.

Paper Details

Date Published: 15 October 2012
PDF: 7 pages
Proc. SPIE 8420, 6th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optical System Technologies for Manufacturing and Testing, 842008 (15 October 2012); doi: 10.1117/12.977625
Show Author Affiliations
Wen-jun Yi, National Univ. of Defense Technology (China)
Hai-bo Liu, National Univ. of Defense Technology (China)
Jian-kun Yang, National Univ. of Defense Technology (China)
Hui Jia, National Univ. of Defense Technology (China)
Li-xin Yang, National Univ. of Defense Technology (China)


Published in SPIE Proceedings Vol. 8420:
6th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optical System Technologies for Manufacturing and Testing
Xiangdi Lin; Yoshiharu Namba; Tingwen Xing, Editor(s)

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