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基于遗传算法的Tiling覆盖策略天文卫星任务规划

徐子羚 刘玉荣 冯准

徐子羚, 刘玉荣, 冯准. 基于遗传算法的Tiling覆盖策略天文卫星任务规划[J]. 空间科学学报, 2022, 42(2): 321-328. doi: 10.11728/cjss2022.02.210112006
引用本文: 徐子羚, 刘玉荣, 冯准. 基于遗传算法的Tiling覆盖策略天文卫星任务规划[J]. 空间科学学报, 2022, 42(2): 321-328. doi: 10.11728/cjss2022.02.210112006
XU Ziling, LIU Yurong, FENG Zhun. Mission Planning for Astronomical Satellite Based on Genetic Algorithm under Tiling Coverage Strategy (in Chinese). Chinese Journal of Space Science, 2022, 42(2): 321-328. DOI: 10.11728/cjss2022.02.210112006
Citation: XU Ziling, LIU Yurong, FENG Zhun. Mission Planning for Astronomical Satellite Based on Genetic Algorithm under Tiling Coverage Strategy (in Chinese). Chinese Journal of Space Science, 2022, 42(2): 321-328. DOI: 10.11728/cjss2022.02.210112006

基于遗传算法的Tiling覆盖策略天文卫星任务规划

doi: 10.11728/cjss2022.02.210112006
基金项目: 中国科学院战略性先导科技专项 (XDA15040100)和北京市科委空间科学实验室培育项目(E0396001)共同资助
详细信息
    作者简介:

    徐子羚:E-mail:xuziling18@mails.ucas.ac.cn

  • 中图分类号: V4

Mission Planning for Astronomical Satellite Based on Genetic Algorithm under Tiling Coverage Strategy

  • 摘要: 天文卫星机遇目标任务规划是一个复杂的多目标优化问题。针对Tiling覆盖策略的机遇目标任务规划要求及其约束条件进行抽象,建立任务规划问题模型,在规划模型基础上设计基于遗传算法的多目标优化任务规划算法TPA,并通过实例数据验证了不同参数条件下的求解。在解决Tiling覆盖策略的天文卫星机遇目标多目标任务规划问题时,所提方法能够在保证算法收敛性的同时兼顾优先级和规划路径,满足规划需求。

     

  • 图  1  染色体编码

    Figure  1.  Example of a chromosome coding

    图  2  TPA规划算法流程

    Figure  2.  Flow chart of TPA algorithm

    图  3  GW170814的Tiling规划轨迹

    Figure  3.  Tiles track after scheduled of GW170814

    图  4  GW170814的时间规划结果

    Figure  4.  Planning results of GW170814

    图  5  TPA算法收敛图像

    Figure  5.  TPA algorithm convergence image

    表  1  数学模型中的变量定义

    Table  1.   Parameters definition

    参数含义
    ${{S}}$ 卫星资源集合
    ${{Z}}$ 观测天区
    $[{{{T}}_{{{\rm{s}}}}},{{{T}}_{{{\rm{e}}}}}]$ ${{{T}}_{{{\rm{s}}}}}$表示规划起始时间,${{{T}}_{{{\rm{e}}}}}$表示规划结束时间
    ${{T}}$ 观测任务目标Tile集合
    ${{W}}$ 可视时间窗口集合
    ${{R}}$ ${{R}}$为规划方案
    下载: 导出CSV

    表  2  输入数据Tile

    Table  2.   Input data of Tile

    Tile 编号赤经/ (deg)赤纬/ (deg)观测时长/min优先级
    146.4754098361–44.2015298511101.91000161867
    245.75–44.9938801505101.82690866131
    347.1774193548–43.4068584859101.80932834628
    446.5254237288–45.7839671618101.70176233296
    ···············
    22844.296875–9.59406822686100.0507893812028
    22943.59375–8.98929934516100.0501842856465
    23045.0–7.78271438539100.0501176647958
    下载: 导出CSV

    表  3  时间窗口的输入数据

    Table  3.   Input data of time windows

    Tile 编号开始时间结束时间持续时间
    123155989231576981709
    123161132231635292397
    123166965231693602395
    123172798231751912393
    ············
    23023230989232337092720
    23023236814232395342720
    2302324263923243347708
    下载: 导出CSV

    表  4  规划结果中Tile优先级

    Table  4.   Tile’s priority in planning results

    规划结果中前n
    Tile占比/(%)
    优先级降序前 n Tile在规划
    结果中前n Tile 的占比/(%)
    2088.24
    5095.24
    8094.03
    10092.86
    下载: 导出CSV
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出版历程
  • 收稿日期:  2021-01-12
  • 录用日期:  2021-04-14
  • 修回日期:  2021-04-30
  • 网络出版日期:  2022-05-25

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