针对现有导航系统中高轨卫星路径损耗大、星地延迟长等缺点,以及传统星座设计约束复杂、结果非最优的问题,采用遗传算法开展低轨导航星座构形优化设计。利用遗传算法对全球星系统(Globalstar)进行构型优化,验证了方法的正确性;结合低轨全球导航星座所受约束,分别使用传统覆盖带设计方法与遗传算法进行星座设计与构型优化。设计结果表明,遗传算法设计方法相较于传统的覆盖带法,星座卫星总数减少了5颗、轨道数减少6条、覆盖重数显著提升,位置精度因子(PDOP)值最大值由7.46降至2.62,可用覆盖率由99.3%以下提升到99.98%以上,验证了遗传算法进行低轨导航星座构型优化的有效性。

Medium earth orbit (MEO) and high earth orbit (HEO) satellite, which are widely used in most of navigation systems, has higher power loss and longer transmission delay than low earth orbit (LEO) satellites. Traditional constellation design has complex constraint functions, and its results are often not the optimal solution. In order to solve these problems, LEO satellites and genetic algorithm (GA) are used to design and optimize the configuration of navigation constellation. Firstly, GA is used to optimize the Globalstar system, and the correctness of this constellation design method is verified. Then, the constraints of LEO global navigation constellation are analyzed. SOC method and GA method are used for constellation configuration optimization. The results show that compared with the SOC method, the satellites number of GA method is reduced by 5, the number of orbits is reduced by 6, the maximum value of PDOP decreases from 7.46 to 2.62, and the coverage rate of PDOP availability increases from less than 99.3% to more than 99.98%. These demonstrates the effectiveness of this approach.