摘要
研究利用进化算法实现低轨区域通信星座的多目标优化设计。首先分析、确定低轨星座优化的轨道控制参数 ,然后将基于 Pareto最优概念的多目标进化算法引入星座优化中。结合星座覆盖性能的评价准则 ,给出了一种利用非劣分层遗传算法 (NSGA- II)实现星座轨道控制参数优化的框架。最后对具体实例进行了优化仿真 ,结果表明 ,该方法可以获得一组分布合理的 Pareto解 。
A multi-object optimization of LEO regional communication constellation based on genetic algorithm was studied. First the orbit control parameters for LEO constellation optimization were analyzed and determined; then multi-object genetic algorithm based on Pareto maximum was introduced into constellation optimization. Combining the coverage assessment criterions, an orbit parameters optimization framework based on nondominated sorting genetic algorithm (NSGA-II) was proposed. This method is applied to a detailed example, and result shows a group of Pareto solutions with good spread can be achieved, which gives strong support to constellation scheme determination.
出处
《解放军理工大学学报（自然科学版）》
EI
2005年第1期1-6,共6页
Journal of PLA University of Science and Technology(Natural Science Edition)
基金
国家自然科学基金资助项目 (60 472 0 5 1)
关键词
卫星星座
多目标优化
遗传算法
satellite constellation
multi-object optimization
genetic algorithm
