基于聚类的密集目标卫星单轨成像规划方法研究  

Research on Single Orbit Satellite Imaging Scheduling Method ofDense Targets Based on Clustering

作　　者：彭玉 张新 王雷[3] 牛馨卿 PENG Yu;ZHANG Xin;WANG Lei;NIU Xinqing(Key Laboratory of Digital Earth Science,Aerospace Information Research Institute,Chinese Academy of Sciences,Beijing 100094,China;College of Resources and Environment,University of Chinese Academy of Sciences,Beijing 100049,China;Key Laboratory of Earth Observation,Aerospace Information Research Institute,Chinese Academy of Sciences,Hainan Research Institute,Sanya 572029,China)

机构地区：[1]中国科学院空天信息创新研究院数字地球重点实验室,北京100094 [2]中国科学院大学资源与环境学院,北京100049 [3]中国科学院空天信息研究院海南研究院海南省地球观测重点实验室,海南三亚572029

出　　处：《测绘与空间地理信息》2023年第6期36-40,共5页Geomatics & Spatial Information Technology

基　　金：海南省重点研发计划(ZDYF2021SHFZ105);国家自然科学基金(41971310)资助。

摘　　要：卫星能量与存储有限,对密集点目标进行观测时,存在观测任务间互斥、需要观测较多次数的问题。针对成像卫星密集点目标任务规划,本文改进了点目标聚类策略,使用改进的最大度团划分方法生成尽量少数量的任务团,同时使获取的任务团优先级之和更大;建立了考虑时间、能量、观测角度等约束的满足模型,为获得更高的观测总收益,并减少侧摆带来的能量损耗,以观测任务优先级之和与平均侧摆角度为优化目标,设计一种考虑基于侧摆优化的启发式蚁群算法对模型进行求解,最后,用仿真实验验证所提出算法的可行性和高效性,为卫星密集点目标任务规划提供技术支持。Satellites have limited energy and storage,when observing dense point targets,there are problems such as mutual exclusion between observation tasks and more observations are required.Aiming at satellite dense point target mission scheduling,the point targets clustering strategy is improved,and the advanced maximum clique partition algorithm is used,generating as few mission groups as possible,and at the same time makes the sum of the acquired mission group priorities higher.A satisfaction model considering constraints such as time,energy and observation angles is established.In order to obtain higher total observation incomes and reduce energy loss caused by attitude maneuver,a heuristic ant colony algorithm based on slew angle optimization is designed to solve the model with the sum of the observation tasks priorities and the average slew angle as the optimization goal.Finally,the feasibility and efficiency of the proposed algorithm are verified by simulation experiments,which can provide technical support for satellite dense point targets mission planning.

关 键 词：密集任务 团划分算法 任务规划 蚁群算法 

分 类 号：P228[天文地球—大地测量学与测量工程]