摘要
在室内覆盖的大量的WiFi信号可以用来室内定位。尽管很多WiFi室内定位技术被提出,但其定位精度仍然未达到实际应用的需求。针对这个问题,该文提出一种自适应仿射传播聚类(AAPC)算法用以提高WiFi指纹的聚类质量,从而提高定位精度。AAPC算法通过动态调整参数生成不同的聚类结果,然后采用聚类有效性指标筛选出其中最佳的。采集大量真实环境数据进行试验,试验结果表明采用AAPC算法产生的聚类结果具有更高的定位精度。
There are a large number of indoor WiFi signals which can be used for indoor positioning. Although many WiFi indoor positioning technology is proposed, it＇s positioning accuracy still does not meet the actual application requirements. For this problem, an Adaptive Affinity Propagation Clustering （AAPC） algorithm is proposed to improve the clustering quality of WiFi fingerprint, thus improving the positioning accuracy. The AAPC algorithm generates different clustering results by dynalnically adjusting parameters, then cluster validity indices are used to select the best ones. A large number of real environmental data are collected and tested. The experimental results show that the clustering results generated by AAPC algorithm have higher positioning accuracy.
作者
胡久松
刘宏立
肖郭璇
徐琨
HU Jiusong;LIU Hongli;XIAO Guoxuan;XU Kun(College of Electrical and Information Engineering,Hunan University,Changsha 410006,China;College of Traffic Engineering,Hunan University of Technology,Zhuzhou 412000,China;State Grid Yueqing Electric Power Supply Company,Yueqing,325600,China)
出处
《电子与信息学报》
EI
CSCD
北大核心
2018年第12期2889-2895,共7页
Journal of Electronics & Information Technology
基金
中央国有资本经营预算项目(财企[2013]470号)
国家自然科学基金(61771191)~~
关键词
WiFi室内定位
自适应仿射传播聚类
聚类有效性指标
WiFi indoor positioning
Adaptive Affine Propagation Clustering （AAPC） algorithm
Clustervalidity indices
