基于深度学习的WLAN指纹定位

2018 IEEE Asia-Pacific Conference on Antennas and Propagation (APCAP) Pub Date : 2018-08-01 DOI:10.1109/APCAP.2018.8538306

S. Aikawa, Shinichiro Yamamoto, M. Morimoto

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引用次数: 12

摘要

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。

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WLAN Finger Print Localization using Deep Learning

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.

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2018 IEEE Asia-Pacific Conference on Antennas and Propagation (APCAP)

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