摘要
给出一种利用改进遗传算法实现低轨区域通信星座优化设计的方法,有效克服了上述困难。首先建立通用的区域覆盖星座模型,确定优化控制参数,并结合低轨星座应用背景对其进行约束。然后给出一种基于网格点统计的星座性能评价准则。为了提高遗传算法对局部最优解的搜索能力,文章提出一种混合遗传算法,该方法在基本遗传算法中加入复形调优算法,并根据优秀个体的分布对参数区间进行调整。将该算法应用于星座模型,建立一套完整的星座优化设计方案。最后对具体实例进行优化仿真,结果表明该方法取得良好的优化结果。
A LEO regional communication constellation optimazation method based on modified genetic algorithm was proposed which overcomed above difficulty efficiently. First,the regional coverage constellation model was constructed, optimazation paremeters was determined and constrained according to the application backgrund of LEO constellation. Then constellation performance evaluation criterion based on grid statistic was proposed. In order to improve calculation accuracy of optimization, a mixed genetic algorithm was proposed, in which complex algorithm and parameter region ajusting was introduced. An integrated constellation optimazation was constructed after applying this algorithm to constellation model. Good result can be achieved by appling this method to a detailed constellation example,
出处
《通信学报》
EI
CSCD
北大核心
2005年第8期122-128,共7页
Journal on Communications
基金
国家自然科学基金资助项目(60472051)
关键词
通信
卫星星座
优化
遗传算法
communication
satellite constellation
optimization
genetic algorithm
