Volume 43 Issue 2
Mar.  2023
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Article Navigation >  Chinese Journal of Space Science  > 2023  >  43(2): 361-368 Open Access
ZENG Erkang, WU Haiyan, FENG Zhun. Sky Area Target of Opportunity Mission Planning Method (in Chinese). Chinese Journal of Space Science, 2023, 43(2): 361-368 doi: 10.11728/cjss2023.02.220225020
Citation: ZENG Erkang, WU Haiyan, FENG Zhun. Sky Area Target of Opportunity Mission Planning Method (in Chinese). Chinese Journal of Space Science, 2023, 43(2): 361-368 doi: 10.11728/cjss2023.02.220225020
shu

Sky Area Target of Opportunity Mission Planning Method

doi: 10.11728/cjss2023.02.220225020 cstr: 32142.14.cjss2023.02.220225020
  • 1.

    National Space Science Center, Chinese Academy of Sciences, Beijing 100190

  • 2.

    University of Chinese Academy of Sciences, Beijing 100049

  • Received Date: 2022-02-24
  • Accepted Date: 2022-05-11
  • Rev Recd Date: 2022-12-12
    • Available Online: 2023-04-10
    Abstract
  • In regard to the planning problem of ToO-MM (a type of sky area Target of Opportunity) for SVOM (Space-based multi-band astronomical Variable Objects Monitor) mission, the constraints and optimization goals are abstracted, the mathematical description model is established, and the algorithm TMHPA (ToO-MM Heuristic Planning Algorithm) based on heuristic strategy is designed. The algorithm aims at maximizing satellite scientific observation benefits and maximizing emergency task response, and considering the influence of satellite attitude adjustment time, the observation tasks and data transmission tasks can be planned. An example is given to verify the effectiveness of this algorithm. The results show that the method executed in this paper is not only able to solve the problem of ToO-MM, but also to ensure the convergence and timeliness. TMHPA can give the target observation sequence of the satellite within the sky area and the time period arrangement for performing data transmission tasks. Compared with GA (Genetic Algorithm) and DEA (Differential Evolution Algorithm), it has a shorter computational time overhead and a smaller attitude adjustment time. The TMHPA algorithm could achieve the rapid response to the target observation, and meet the design requirements as well.

     

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