D-watch: Embracing "bad" multipaths for device-free localization with COTS RFID devices

Device-free localization, which does not require any device attached to the target is playing a critical role in many applications such as intrusion detection, elderly monitoring, etc. This paper introduces D-Watch, a device-free system built on top of low cost commodity-off-the-shelf (COTS) RFID ha...

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Bibliographic Details
Main Authors: WANG, Ju, Jie XIONG, JIANG, Hongbo, CHEN, Xiaojiang, FANG, Dingyi
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2016
Subjects:
AoA
Online Access:https://ink.library.smu.edu.sg/sis_research/3386
https://ink.library.smu.edu.sg/context/sis_research/article/4387/viewcontent/D_Watch_2016_pv_oa.pdf
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Institution: Singapore Management University
Language: English
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Summary:Device-free localization, which does not require any device attached to the target is playing a critical role in many applications such as intrusion detection, elderly monitoring, etc. This paper introduces D-Watch, a device-free system built on top of low cost commodity-off-the-shelf (COTS) RFID hardware. Unlike previous works which consider multipaths detrimental, D-Watch leverages the "bad" multipaths to provide a decimeter level localization accuracy without offline training. D-Watch harnesses the angle-of-arrival (AoA) information from the RFID tags' backscatter signals. The key intuition is that whenever a target blocks a signal's propagation path, the signal power experiences a drop which can be accurately captured by the proposed novel P-MUSIC algorithm. The wireless phase calibration scheme proposed does not interrupt the ongoing communication. Real-world experiments demonstrate the effectiveness of D-Watch. In a rich-multipath library environment, D-Watch can localize a human target at a median accuracy of 16.5 cm. In a table area of 2 m×2 m, D-Watch can track a user's fist at a median accuracy of 5.8 cm. D-Watch is capable of localizing multiple targets which is well known to be challenging in passive localization