Volume 42 Issue 1
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Jin Yan, Jiang Jie, Zhang Guangjun. Highly dynamic star tracking algorithm[J]. Infrared and Laser Engineering, 2013, 42(1): 212-217.
Citation: Jin Yan, Jiang Jie, Zhang Guangjun. Highly dynamic star tracking algorithm[J]. Infrared and Laser Engineering, 2013, 42(1): 212-217.

Highly dynamic star tracking algorithm

  • Received Date: 2012-05-05
  • Rev Recd Date: 2012-06-03
  • Publish Date: 2013-01-25
  • The character of high dynamic star sensor's sky image and the deficiency of existing star tracking algorithm at home and abroad were presented. Aiming at these deficiencies, a new star tracking algorithm based on Kalman prediction was put forward. The model of stars' movement was set up based on the character of the star sensor's movement. The adaptive Kalman filter was used to predict the position of the reference stars. The star was matched and tracked by Star Neighborhood Approach. At the end of the article, the prediction and tracking results were presented. The experiment results indicate that the star position prediction errors are less than 5 pixels under the dynamic condition of 5()/s, and the success rate of tracking is up to 95%. The method can adapt for high dynamic star sensor and improve the success rates of tracking availably.
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    [3] Wei Xinguo, Zhang Guangjun, Fan Qiaoyun, et al. Ground function test methods of star sensor using simulated sky image[J]. Infrared and Laser Engineering, 2008, 37(6): 1087-1091. (in Chinese)
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    [9] Jin Yan, Jiang Jie, Zhang Guangjun. A star extraction method for high dynamic star sensor[J]. Infrared and Laser Engineering, 2011, 40(11): 1185-1189. (in Chinese)
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    [18] Jiang Jie, Li Xiao, Zhang Guangjun, et al. A fast star tracking method in star sensor[J]. Journal of Astronautics, 2006, 27(5): 952-955. (in Chinese)
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    [20] Jiang Jie, Zhang Guangjun, Li Xiao, et al. A fast star tracking algorithm for star sensor[J]. Acta Aeronautica et Astronutica Sinica, 2006, 27(5): 913-916. (in Chinese)
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    [22] Jie J, Zhang G J, Wei X G, et al. Rapid star tracking algorithm for star sensor[J]. IEEE A E Systems Magzine, 2009, 24(9): 23-33.
    [23] Samaan M A. Toward faster and more accurate star sensors using recursive centroiding and star identification[D]. Texas: Dept Texas A M University, 2006.
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Highly dynamic star tracking algorithm

  • 1. Key Laboratory of Precision Opto-mechatronics Technology of Education,School of Instrumental Science and Optoelectronics Engineering,Beihang University,Beijing 100191,China

Abstract: The character of high dynamic star sensor's sky image and the deficiency of existing star tracking algorithm at home and abroad were presented. Aiming at these deficiencies, a new star tracking algorithm based on Kalman prediction was put forward. The model of stars' movement was set up based on the character of the star sensor's movement. The adaptive Kalman filter was used to predict the position of the reference stars. The star was matched and tracked by Star Neighborhood Approach. At the end of the article, the prediction and tracking results were presented. The experiment results indicate that the star position prediction errors are less than 5 pixels under the dynamic condition of 5()/s, and the success rate of tracking is up to 95%. The method can adapt for high dynamic star sensor and improve the success rates of tracking availably.

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