WLAN Finger Print Localization using Deep Learning

被引：0

作者：

Aikawa, Satoru ^{[1
]}

Yamamoto, Shinichiro ^{[1
]}

Morimoto, Masakazu ^{[1
]}

机构：

[1] Univ Hyogo, Grad Sch Engn, Himeji, Hyogo, Japan

来源：

PROCEEDINGS OF THE 2018 IEEE 7TH ASIA-PACIFIC CONFERENCE ON ANTENNAS AND PROPAGATION (APCAP) | 2018年

关键词：

Localization; WLAN; Finger Print; Deep Learning; INDOOR FINGERPRINTING LOCALIZATION;

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：

Navigation applications for smartphones are poplar system, recently. Especially, WLAN Finger Print technique is suitable for indoor environment where GPS is difficult to use. This contribution describes a Finger Print Localization scheme using Deep Learning technique. First, the principle and experimental results of Finger Print using Deep Learning are described. Second, Coarse-to-Fine Localization based on SOM is proposed. A scheme to guess ahead accuracy for WLAN/GPS switching is described in the last section.

引用

页码：541 / 542

页数：2

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