全球定位系统2016，Vol.41Issue(5)：89-92,4.DOI:10.13442/j.gnss.1008-9268.2016.05.018
一种基于位置指纹定位的K-均值聚类算法的改进
Research on an Algorithm of Fingerprint Location Based on K-means and WKNN
孔港港 1杨力 2孙聃石 1吴雨2
作者信息
- 1. 信息工程大学 导航与空天目标工程学院，郑州，450001
- 2. 北斗导航应用技术河南省协同创新中心，郑州 450001
- 折叠
摘要
Abstract
K-mean clustering algorithm based on fingerprint is divided the reference point into K subclass.The similar objects are clustered together to reduce the search space and im-prove the efficiency.In this paper,we weighted the nearest neighbor of the choose subclass based on the K-means clustering algorithm.Increase the proportion of high correlation refer-ence point while calculating,so as to achieve the purpose of improving the accuracy of loca-tion.The experimental results show that the accuracy of the new algorithm has improved 18.5 percent.关键词
指纹定位/K-均值聚类/加权Key words
Fingerprint localization/K-means clustering/weighting分类
天文与地球科学引用本文复制引用
孔港港,杨力,孙聃石,吴雨..一种基于位置指纹定位的K-均值聚类算法的改进[J].全球定位系统,2016,41(5):89-92,4.
