基于K均值聚类的新型选星算法  

A New Satellite Selection Algorithm Based on K-means

作　　者：董天宝 唐健 曾芳玲 DONG Tian-bao;TANG Jian;ZENG Fang-ling(Institute of Electronic Countermeasure,National University of Defense Technology,Hefei Anhui 230037,China)

机构地区：[1]国防科技大学电子对抗学院,安徽合肥230037

出　　处：《计算机仿真》2022年第11期22-26,共5页Computer Simulation

基　　金：国家自然科学基金面上项目(62071479)。

摘　　要：在进行导航定位时,第一步是进行卫星的选取,选取卫星的合适与否直接决定了导航定位的准确性。为了提高选星的精确性和时效性,在计算卫星方位角和仰角的基础上,提出了一种新型选星算法——基于K均值聚类的新型选星算法。在选取最大仰角卫星的基础上利用K均值聚类算法对可见卫星的方位角进行聚类选星,并利用MATLAB软件进行仿真。仿真结果表明:上述算法选星的GDOP值与最佳几何精度因子法得到的GDOP值相差无几,具有较高的精确性,同时算法计算复杂度大大减小,提高了选星的时效性。During navigation and positioning,the first step is to select satellites,which determines the accuracy of navigation and positioning directly.In order to improve the accuracy and the real-time performance of the algorithm,a new satellite selection algorithm based on K-means clustering is proposed on the basis of calculating the azimuth and elevation of satellites.On the basis of selecting the satellite with the highest elevation angle,this paper uses the K-means algorithm to cluster the azimuth angle to select satellites and uses MATLAB software to simulate.The simulation results show that the GDOP value of the algorithm is almost the same as that obtained by the optimal geometric precision factor method,which has high accuracy,while the computational complexity of the algorithm is greatly reduced and the timeliness of satellite selection is improved.

关 键 词：方位角 仰角 选星 仿真 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]