NDLI: LiFS: low human-effort, device-free localization with fine-grained subcarrier information

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LiFS: low human-effort, device-free localization with fine-grained subcarrier information

Content Provider	ACM Digital Library
Author	Jiang, Hongbo Fang, Dingyi Xie, Binbin Wang, Ju Xiong, Jie Chen, Xiaojiang Jamieson, Kyle
Abstract	Device-free localization of people and objects indoors not equipped with radios is playing a critical role in many emerging applications. This paper presents an accurate model-based device-free localization system LiFS, implemented on cheap commercial off-the-shelf (COTS) Wi-Fi devices. Unlike previous COTS device-based work, LiFS is able to localize a target accurately without offline training. The basic idea is simple: channel state information (CSI) is sensitive to a target's location and by modelling the CSI measurements of multiple wireless links as a set of power fading based equations, the target location can be determined. However, due to rich multipath propagation indoors, the received signal strength (RSS) or even the fine-grained CSI can not be easily modelled. We observe that even in a rich multipath environment, not all subcarriers are affected equally by multipath reflections. Our pre-processing scheme tries to identify the subcarriers not affected by multipath. Thus, CSIs on the "clean" subcarriers can be utilized for accurate localization. We design, implement and evaluate LiFS with extensive experiments in three different environments. Without knowing the majority transceivers' locations, LiFS achieves a median accuracy of 0.5 m and 1.1 m in line-of-sight (LoS) and non-line-of-sight (NLoS) scenarios respectively, outperforming the state-of-the-art systems. Besides single target localization, LiFS is able to differentiate two sparsely-located targets and localize each of them at a high accuracy.
Starting Page	243
Ending Page	256
Page Count	14
File Format	PDF EPUB
ISBN	9781450342261
DOI	10.1145/2973750.2973776
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-10-03
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Multipath Low human-effort Device-free localization Power fading model Channel state information
Content Type	Text
Resource Type	Article

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