Indoor Fingerprint Localization Based on Fuzzy C-means Clustering

被引：21

作者：

Zhou, Hao ^{[1
]}

Nguyen Ngoc Van ^{[2
]}

机构：

[1] Tongji Univ, Sch Elect & Informat Engn, Shanghai 200092, Peoples R China

[2] Hanoi Univ Sci & Technol, Sch Elect & Telecommun, Hanoi, Vietnam

来源：

2014 SIXTH INTERNATIONAL CONFERENCE ON MEASURING TECHNOLOGY AND MECHATRONICS AUTOMATION (ICMTMA) | 2014年

关键词：

WiFi localization; fingerprint; fuzzy c-means clustering;

D O I：

10.1109/ICMTMA.2014.83

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Accuracy of the global positioning system (GPS) cannot meet the demand of indoor service. To address this issue, a radio frequency (RF) based system named RADAR for locating and tracking users inside buildings is presented, using fingerprint architecture. However, the traditional system is still sensitive to multipath and body movement. Furthermore, it costs much computing time. In this paper, we propose a fingerprint algorithm based on fuzzy c-means clustering. It uses clustering to reduce the computing time. We have evaluated the system in underground parking area. The results show that the technique reduces the computing time below a reasonable degree and enhances the accuracy of previous system slightly.

引用

页码：337 / 340

页数：4

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