WLAN Finger Print Localization using Deep Learning

S. Aikawa, Shinichiro Yamamoto, M. Morimoto
{"title":"WLAN Finger Print Localization using Deep Learning","authors":"S. Aikawa, Shinichiro Yamamoto, M. Morimoto","doi":"10.1109/APCAP.2018.8538306","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":198124,"journal":{"name":"2018 IEEE Asia-Pacific Conference on Antennas and Propagation (APCAP)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE Asia-Pacific Conference on Antennas and Propagation (APCAP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APCAP.2018.8538306","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12

Abstract

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.
基于深度学习的WLAN指纹定位
最近,智能手机的导航应用程序非常流行。特别是WLAN指纹识别技术适用于GPS难以使用的室内环境。本文描述了一种使用深度学习技术的指纹定位方案。首先,介绍了基于深度学习的指纹识别原理和实验结果。其次,提出了基于SOM的从粗到精定位方法。最后一节描述了一种预测WLAN/GPS交换精度的方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信