基于多目标遗传算法的多星座选星方法  

Satellite Selection with Multi-Objective Genetic Algorithm for Multi-GNSS Constellations

作　　者：徐小钧[1,2] 马利华 艾国祥[1] 

机构地区：[1]中国科学院国家天文台,北京100012 [2]中国科学院大学,北京100049

出　　处：《上海交通大学学报》2017年第12期1520-1528,共9页Journal of Shanghai Jiaotong University

基　　金：国家自然科学基金项目(11573041;11473045);中国科学院重点部署项目(KJCX2-EW-J01)资助

摘　　要：为了提高接收机导航定位的实时性,需要从大量的可见卫星中选取几何布局较好的星座组合进行定位解算.提出多星座选星可以作为有约束条件的离散型多目标优化问题求解,并基于NSGA-Ⅱ遗传算法提出了一种多星座选星方法.该方法能综合优化几何精度因子(GDOP)和选星数目,可以在减少接收机运算量的同时获得良好的定位精度.仿真结果表明,利用该方法在静态和动态情况下均有良好的有效性和实时性.With the development of multi-global navigation satellite system（GNSS）constellations,more and more satellites will be available.To ensure the accuracy of positioning,we have to select optimal satellites to improve the real-time performance of the receiver.In this paper,we firstly consider that satellite selection of multi-GNSS constellation can be used as a discrete multi-objective optimization problem with constraint conditions,and a new method based on non-dominated sorting genetic algorithm（NSGA）-Ⅱ is proposed.This method can comprehensively optimize the geometric dilution of precision（GDOP）and the number of selected satellites at the same time.We can obtain good positioning accuracy while reducing the amount of computation of the receiver.The simulation results show that the proposed method is effective in both static and dynamic conditions with good real-time capabilities.

关 键 词：选星 多目标优化 NSGA-Ⅱ算法 几何精度因子 多导航星座 

分 类 号：P151[天文地球—天文学]