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天区机遇目标空间探测任务规划算法

曾而康 吴海燕 冯准

曾而康, 吴海燕, 冯准. 天区机遇目标空间探测任务规划算法[J]. 空间科学学报, 2023, 43(2): 361-368. doi: 10.11728/cjss2023.02.220225020
引用本文: 曾而康, 吴海燕, 冯准. 天区机遇目标空间探测任务规划算法[J]. 空间科学学报, 2023, 43(2): 361-368. doi: 10.11728/cjss2023.02.220225020
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

天区机遇目标空间探测任务规划算法

doi: 10.11728/cjss2023.02.220225020
基金项目: 中国科学院战略性先导科技专项项目资助(XDA15040100, XDA15040400)
详细信息
    作者简介:

    吴海燕:E-mail:why@nssc.ac.cn

  • 中图分类号: V4

Sky Area Target of Opportunity Mission Planning Method

  • 摘要: 针对中法合作SVOM卫星的天区范围内机遇目标规划问题(ToO-MM),对其中的约束条件和优化目标进行抽象,建立了规划问题数学模型,设计实现了基于启发式规则的机遇目标规划算法TMHPA。以最大化卫星科学观测收益和最大化应急任务响应度为优化目标,考虑卫星姿态调整时间的影响,对观测任务和数传任务进行规划。通过仿真实验验证算法的有效性,结果表明该方法能够在保证算法收敛性和时效性同时,给出卫星在天区范围内的网格单元(tile)目标观测序列以及执行数传任务的时段安排,实现对ToO目标观测的快速响应,并及时下传机遇目标科学观测数据,满足规划算法的设计需求。

     

  • 图  1  TMHPA算法流程

    Figure  1.  Flow chart of TMHPA

    图  2  TMHPA算法在GW170814上的规划结果

    Figure  2.  TMHPA planning result on GW170814

    图  3  姿态调整过程

    Figure  3.  Process of slew

    表  1  ToO-MM规划模型基本符号定义

    Table  1.   Parameter definition of ToO-MM model

    符号描述
    T机遇目标tile集合
    W目标可视时间窗口
    G地面数传站可视窗口
    R观测任务规划结果
    K数传任务规划结果
    Ntile的总数量
    S姿态调整时长
    E姿态调整时段
    C一个圈次观测tile数量
    O存储量
    下载: 导出CSV

    表  2  GW170814天区机遇目标tile数据

    Table  2.   Tile data of GW170814

    编号赤经/(º)赤纬/(º)观测时长/min观测优先级
    147.857142–42.609806101.589328
    245.775862–46.571847101.553358
    346.428571–42.609806101.425764
    447.950812–44.201529101.415292
    ···············
    22835.816326–53.572233100.068670
    22939.919354–43.406858100.066731
    23050.901639–44.201529100.066025
    下载: 导出CSV

    表  3  TMPHA规划结果

    Table  3.   Planning result of TMPHA

    年-月-日时刻 (UT)积秒编号圈次持续时长/s调姿时间/s
    2022-09-2601:24:562316029643975733108
    2022-09-2602:15:252316332553976600104
    2022-09-2602:27:092316402973976600105
    2022-09-2602:38:542316473463976600108
    ·····················
    2022-09-2623:39:3023240370563989600113
    2022-09-2623:51:2323241083573989600105
    2022-09-2700:03:0823241788603989958105
    下载: 导出CSV

    表  4  各个优化目标函数值

    Table  4.   Value of each optimization objective function

    优化目标$ {f}_{\mathrm{p}\mathrm{r}\mathrm{o}} $$ {f}_{\mathrm{s}\mathrm{l}\mathrm{e}\mathrm{w}} $$ {f}_{\mathrm{p}\mathrm{r}\mathrm{i}} $F
    数值0.01240.0280.0430.0641
    下载: 导出CSV

    表  5  算法对比结果

    Table  5.   Comparison results of algorithm

    算法GADEATMHPA
    总观测收益54.1752.3250.90
    卫星调姿用时/s8502.118471.838199.36
    算法总耗时/s144.31135.453.78
    下载: 导出CSV
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出版历程
  • 收稿日期:  2022-02-24
  • 录用日期:  2022-05-11
  • 修回日期:  2022-12-12
  • 网络出版日期:  2023-04-10

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