摘要
面向应急条件下的观测需求,为提高成像任务完成效率,对敏捷成像卫星密集任务聚类问题进行研究。分析了敏捷成像卫星观测过程,给出了任务聚类的俯仰、翻滚观测摆角及任务间过渡时间约束。建立了聚类图模型,给出了模型的构建算法。设计了一种基于最大最小蚂蚁系统的聚类算法,结合聚类模型特点设计蚁群策略,并对重叠和冲突的聚类任务进行处理。实验算例验证了模型和算法的有效性。
Considering observing requirements in emergency,the observing task clustering problem of an agile imaging satellite is studied in order to improve the completion efficiency of the tasks.By analyzing the observing process,the clustering constrains,such as pitching and rolling angular restricts and transition time constrain,are given.A clustering graph method is proposed,and the model construction algorithm is given.A clustering algorithm based on the max-min ant system（MMAS） is designed to solve the problem.The ant colony search strategy is designed according to the model.The overlap and conflict of clustering tasks are also considered.Simulation results show the efficiency of the model and the proposed algorithm.
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2012年第5期931-935,共5页
Systems Engineering and Electronics
基金
国家安全重大基础研究项目(6136101)资助课题
关键词
任务聚类
建模
蚁群算法
敏捷成像卫星
应急观测任务
task clustering
modeling
ant colony algorithm
agile imaging satellite
emergency observing task
