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低轨(LEO,Low Earth Orbit)通信星座的特殊功能决定了其构型优化需要综合考虑成本、覆盖和路由性能等因素.以往的研究往往忽略了路由性能,导致优化得到的构型不能很好的满足要求.首先给出了两个意义明确的星座路由性能的评价指标,然后通过将它们作为目标函数进行仿真,验证了其优化必要性和评价有效性.最后利用多目标遗传算法实现了星座的构型优化.仿真结果显示,将路由算法加入到星座的构型优化中,在仅对星座构型参数进行微调的前提下,不仅满足了成本、覆盖等基本要求,而且星座的路由性能大大提高.
The special function of LEO (Low Earth Orbit) communication constellation determines that its configuration optimization needs to consider factors such as cost, coverage and routing performance, etc. Previous studies often neglected routing performance and resulted in poorly optimized configurations We first give two meaningful evaluation indexes of constellation routing performance, and then verify their necessity of optimization and evaluation validity by simulating them as objective function.Finally, constellation is realized by using multi-objective genetic algorithm The simulation results show that the routing algorithm is added to the constellation configuration optimization, and only fine tuning of constellation configuration parameters not only meets the basic requirements such as cost and coverage, but also constellation routing performance greatly improve.