Volume 42 Issue 5
Oct.  2022
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LEI Xiangxu, XIA Shengfu, YANG Yang, WANG Xiaozhen, ZHANG Zhengyuan, LI Zhenwei, SANG Jizhang. Comparison of Initial Orbit Determination Methods with Very-Short-Arc Angle Observations from LEO Space Debris (in Chinese). Chinese Journal of Space Science, 2022, 42(5): 984-990 doi: 10.11728/cjss2022.05.211026108
Citation: LEI Xiangxu, XIA Shengfu, YANG Yang, WANG Xiaozhen, ZHANG Zhengyuan, LI Zhenwei, SANG Jizhang. Comparison of Initial Orbit Determination Methods with Very-Short-Arc Angle Observations from LEO Space Debris (in Chinese). Chinese Journal of Space Science, 2022, 42(5): 984-990 doi: 10.11728/cjss2022.05.211026108

Comparison of Initial Orbit Determination Methods with Very-Short-Arc Angle Observations from LEO Space Debris

doi: 10.11728/cjss2022.05.211026108 cstr: 32142.14.cjss2022.05.211026108
  • Received Date: 2021-10-26
  • Accepted Date: 2022-04-11
  • Rev Recd Date: 2022-05-07
  • Available Online: 2022-09-22
  • Optical observation is the most common observation method for space objects. When optical telescopes work in scanning mode, the obtained observation arc length is usually very short, even less than 1% of the orbital period of the observed space object. And such angle observation arc is called Very-Short-Arc (VSA) angle observation. Based on the VSA of the near-circular LEO space debris, this paper studies the performance differences of commonly used methods for initial orbit determination. The influence of observation arc length on the success rate and error of different initial orbit determination algorithms is analyzed. The results can provide reference for initial orbit determination. Several commonly used methods, such as Laplace method, Gauss method, Gooding method and Range-Search (RS) algorithm, proposed in recent years, are compared and analyzed. The results of large-scale VSA show that the success rate of the RS algorithm is higher than 90%, and the statistical error of the semi-major axis of the initial orbit elements is only 25 km. Results show that the succeed rate of RS method is better than other algorithms. The research results can provide reference for subsequent observation data processing.

     

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