Efficient WiFi Fingerprint Training Using Semi-supervised Learning

被引:0
|
作者
Yuan, Ye [1 ]
Pei, Ling [1 ]
Xu, Changqing [1 ]
Liu, Qianchen [1 ]
Gu, Tingyu [1 ]
机构
[1] Shanghai Jiao Tong Univ, Sch Elect Informat & Elect Engn, Shanghai Key Lab Nav & Locat Based Serv, Shanghai 200240, Peoples R China
关键词
fingerprint; indoor localization; continuously sampling; semi-supervise learning; Gaussian Processes;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Fingerfrinting based WiFi positioning approach needs an off-line training phase to build a radio map with received signal strength indication vector of each reference point. In existing systems, this training phase may cost a tremendous amount of workload to achieve satisfying location result. To cut down on the workload notably and guarantee the location result in the meantime, we will introduce an efficient WiFi fingerprint training method: Fa-Fi namely fast fingerprint generation, which uses semi-supervised learning in this article. This proposed method can reduce the training phase time cost to about 1/5, and guarantee the localization accuracy at the same time.
引用
收藏
页码:148 / 155
页数:8
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