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中国电子科技集团公司第五十四研究所,河北 石家庄 050081
[ "林晓勇(1985- ),男,中国电子科技集团公司第五十四研究所高级工程师,主要研究方向为系统总体设计、云+网+端体系架构设计、管控业务中台设计等。" ]
[ "王港(1990- ),男,中国电子科技集团公司第五十四研究所高级工程师,主要研究方向为遥感智能处理、卫星任务规划、航天地面系统等。" ]
[ "刘晓丽(1976- ),女,中国电子科技集团公司第五十四研究所教授级高级工程师,主要研究方向为卫星任务规划。" ]
[ "高朝晖(1972- ),男,中国电子科技集团公司第五十四研究所副总工程师,教授级高级工程师,主要研究方向为航天测运控及应用领域系统总体设计、工程研发与项目管理。" ]
收稿:2025-05-06,
修回:2025-07-30,
纸质出版:2025-09-20
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林晓勇,王港,刘晓丽等.面向应急的航天对地观测资源联合任务规划算法架构研究[J].天地一体化信息网络,2025,06(03):1-9.
LIN Xiaoyong,WANG Gang,LIU Xiaoli,et al.Research on Emergency-Oriented Joint Mission Planning Algorithm for Space Resources[J].Space-Integrated-Ground Information Networks,2025,06(03):1-9.
林晓勇,王港,刘晓丽等.面向应急的航天对地观测资源联合任务规划算法架构研究[J].天地一体化信息网络,2025,06(03):1-9. DOI: 10.11959/j.issn.1000-0801.2025023.
LIN Xiaoyong,WANG Gang,LIU Xiaoli,et al.Research on Emergency-Oriented Joint Mission Planning Algorithm for Space Resources[J].Space-Integrated-Ground Information Networks,2025,06(03):1-9. DOI: 10.11959/j.issn.1000-0801.2025023.
为实现面向应急突发事件的航天对地观测资源整合,快速调动各类航天对地观测资源在指定时间内及时高效实施应急观测任务,提出面向应急的航天对地观测资源联合任务规划算法架构。针对现有航天应急任务实施过程中存在的资源冲突、资源协调难、动态响应能力差等问题,设计了资源透明共享、一键式快速任务规划的航天对地观测联合任务规划思路,构建了灵活可扩展的统一调度控制运行架构,实现资源监视、需求筹划、约束检验和快速响应。经过演习演练和实验分析,算法经业务化部署与迭代优化后,任务覆盖率提升到95%,响应时间提升到15 min,有效提升了各类航天对地观测资源的应急响应能力。
To achieve the integration of space to ground observation resources for emergency situations
and to quickly mobilize various space to ground observation resources to implement emergency observation tasks in a timely and efficient manner within a specified time
a joint task planning algorithm architecture for emergency space resources is proposed. Aiming at the problems of resource conflicts
difficulty in resource coordination
and poor dynamic response capabilities in the implementation of existing aerospace emergency missions
a joint mission planning approach for space to earth observation is designed
which includes transparent resource sharing and one click rapid task planning. A flexible and scalable unified scheduling and control operation architecture is constructed to achieve resource monitoring
demand planning
constraint testing
and rapid response. After conducting exercises and experimental analysis
the algorithm has been deployed and iteratively optimized for business purposes
resulting in a task coverage rate of 95% and a response time of 15 minutes
effectively enhancing the emergency response capabilities of various aerospace earth observation resources.
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