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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 and so on. This paper introduces D-Watch, a device-free system built on the top of low cost commodity-off-the-shelf 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 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 detected by the proposed novel P-MUSIC algorithm. The proposed wireless phase calibration scheme does not interrupt the ongoing data communication and thus reduces the deployment burden. We implement and evaluate D-Watch with extensive experiments in three different environments. D-Watch achieves a median accuracy of 16.5 cm for library, 25.5 cm for laboratory, and 31.2 cm for hall environment, outperforming the state-of-the-art systems. In a table area of 2 m$x$2 m, D-Watch can track a user's fist at a median accuracy of 5.8 cm. D-Watch is also capable of localizing multiple targets which is well known to be challenging in passive localization.


Antennas, AoA, Calibration, Device-free localization, Estimation, multipath, Multiple signal classification, RFID tags, Target tracking, Intrusion detection, Target tracking, Watches, Commodity off the shelves, Device-free localizations, Localization accuracy, Multipath, Multiple signal classification, Passive localization, RF-ID tags, State-of-the-art system, Radio frequency identification (RFID)


Databases and Information Systems | Software Engineering


IEEE/ACM Transactions on Networking

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Institute of Electrical and Electronics Engineers (IEEE) / Association for Computing Machinery (ACM)

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

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