面向测控数传资源一体化场景的卫星地面站资源多目标优化方法

Multi-objective optimization method oriented to integrated scenario of TT&C resources and data transmission resources

近年来,随着电子技术的发展,地面站测控设备与数传设备逐渐趋同,呈现出功能一体化的特性,充分利用该特性可有效提高地面站设备资源的利用率,缓解星地通信中地面站资源相对匮乏的现实难题。针对问题特征和实际需求,建立了以最小化任务冲突时长、最大化天线负载均衡度以及最大化任务集聚度为优化目标的约束满足模型,提出了面向测控数传资源一体化场景的卫星地面站资源规划多目标优化算法KG-NSGA-II-TTC&DT。该算法针对优化目标设计了负载均衡算子、任务集聚算子以及迭代修复冲突消解算子,并以膝点引导算法进程,有效提升了问题求解的优化性和针对性。实验结果表明,与NSGA-II-TTC&DT算法相比,KG-NSGA-II-TTC&DT在世代距离(GD)指标上实现了16.75%的平均性能提升,在最小化任务冲突时长、最大化天线负载均衡度以及最大化任务集聚度3个优化目标上分别实现了6.67%、9.28%以及1.87%的平均优化性能提升,其中负载均衡算子、任务集聚算子以及迭代修复冲突消解算子的优化性能贡献率分别为31.50%、15.60%、70.57%。

With the development of the electronic technology in recent years,TT&C resources and data transmission resources in satellite ground stations are gradually converging,showing the characteristic of functional integration.Making full use of this feature can effectively improve the utilization rate of satellite ground station resources and alleviate the problem of satellite ground station resource shortage in satellite-to-ground communications.In view of the characteristics of the problem and actual requirements,a constraint satisfaction model is established with the optimization objectives of minimizing taskconflict time,maximizing load-balance degree,and maximizing task-clustering degree.A satellite range scheduling method named KG-NSGA-II-TTC&DT is proposedfor the integrated scenario of TT&C resources and data transmission resources.The load-balance operator,task-clustering operator,and conflict-resolution operator based on iterative repair are designed in the algorithm.The knee point is also used to guide the process of the algorithm,which effectively improves the optimization and pertinence.Experimental results show that compared with the NSGA-II-TTC&DT,the KG-NSGA-II-TTC&DT achieves an average performance improvement of 16.75%in the Generation Distance(GD)indicator,and an improvement of 6.67%,9.28% and 1.87%in the three optimization objectives of minimizing task conflict time,maximizing load-balance degree,and maximizing task clustering degree,respectively.The contribution rate of the load-balance operator,task clustering operator,and conflict resolution operator based on iterative repair is 31.50%,15.60%,and 70.57%,respectively.