基于GDE3算法的侦察卫星星座优化设计

Optimization of Regional Coverage Reconnaissance Satellite Constellation by GDE3 Algorithm

针对区域覆盖的卫星星座优化设计,将一种基于Pareto最优概念的通用差异演化算法(GDE3)应用于区域覆盖型侦察卫星星座的多目标优化设计,并利用多属性决策中的字典序法,根据目标的重要程度,在得到的Pareto解中进行选择。最后,利用STK和VisualC++针对侦察卫星星座进行了仿真,仿真结果表明了该算法可以找到多个Pareto解,避免了传统求解方法的权值选择问题,并且较简单遗传算法具有更好的灵活性,为解决星座优化与设计问题提供了新的思路。

A new method to design regional coverage satellite constellation was proposed, applying the developed version of Generalized Differential Evolution algorithm （GDE3） based on Pareto optimal to the optimization of regional coverage reconnaissance satellite constellation. The best solution, depending on the importance of different objects, was selected via a kind of multi attributes decision method. The results of the simulation realized by STK and Visual C＋＋ show that the algorithm can get a group of Pareto solutions. The algorithm proposed can avoid to select weight of multiple objects. On the other hand, compared with the simple genetic algorithm, the algorithm is more active. Thus this method provides a new idea for solving the question of optimization of satellite constellation with multiple objectives.