摘要
考虑到低轨卫星星座的庞大规模和漫长的建设周期,加之技术和成本的双重挑战,一次性全面部署变得不切实际,这限制了星座在建设过程中的实用性。提出了一种基于遗传算法的逐步优化(Genetic Algorithm-Progressive Optimality,GA-PO)星座设计方法。该方法通过遗传算法生成适合目标区域的最优星座,进行采用逐步优化方法分阶段、分区域实现全球星座的构建。结果表明,逐步建设过程中,在中国、亚洲和全球的可见星数分别达到7、10、12颗,优化星座与北斗三号卫星系统结合后在全球的PDOP值达到了0.9,可见卫星数量达到了25颗。GA-PO方法在满足现有星座构建方案精度的同时,还能够兼顾星座建设过程中在中国和亚洲地区的实用性能。
Considering the large scale and long construction period of LEO satellite constellations,coupled with the dual challenges of technology and cost,it became impractical to fully deploy them at one time,which limited the practicality of the constellations in the construction process.A Genetic Algorithm-Progressive Optimality(GA-PO)constellation design method based on genetic algorithm is proposed.The method generates the optimal constellation suitable for the target region through the genetic algorithm,and proceeds to realize the construction of global constellations by stages and regions using the step-by-step optimization method.The results show that the number of visible satellites in China,Asia and the world during the step-by-step construction process reaches 7,10 and 12,respectively,and the global PDOP value of the optimized constellation combined with the BeiDou-3 satellite system reaches 0.9,and the number of visible satellites reaches 25.The GA-PO method can satisfy the precision of the existing constellation construction scheme while taking into account the practical performance of the constellation construction process in China and Asia.
作者
王启帆
赵兴旺
WANG Qifan;ZHAO Xingwang(School of Spatial Information and Geomatics Engineering,Anhui University of Science and Technology,232001,Huainan,Anhui,PRC)
出处
《江西科学》
2025年第1期140-147,共8页
Jiangxi Science
基金
安徽省自然科学基金项目(2208085MD101)。
关键词
低轨卫星
星座优化
遗传算法
逐步优化
导航增强
low-orbit satellites
constellation optimization
genetic algorithms
step-by-step optimization
navigation enhancements
