Accurate Device-Free Tracking Using Inexpensive RFIDs

Sensors
Liyao LiFeng Chen

Abstract

Without requiring targets to carry any device, device-free-based tracking is playing an important role in many emerging applications such as smart homes, fitness tracking, intruder detection, etc. While promising, current device-free tracking systems based on inexpensive commercial devices perform well in the training environment, but poorly in other environments because of different multipath reflections. This paper introduces RDTrack, a system that leverages changes in Doppler shifts, which are not sensitive to multipath, to accurately track the target. Moreover, RDTrack identifies particular patterns for fine-grained motions such as turning, walking straightly, etc., which can achieve accurate tracking. For the purpose of achieving a fine-grained device-free tracking system, this paper builds a trajectory estimating model using HMM (Hidden Markov Model) to improve the matching accuracy and reduce the time complexity. We address several challenges including estimating the tag influenced time period, identifying moving path and reducing false positives due to multipath. We implement RDTrack with inexpensive commercial off-the-shelf RFID (Radio Frequency IDentification) hardware and extensively evaluate RDTrack in a lobby, stai...Continue Reading

References

Mar 17, 2015·IEEE Transactions on Bio-medical Engineering·Gabriele Ligorio, Angelo M Sabatini
Sep 10, 2015·IEEE Transactions on Pattern Analysis and Machine Intelligence·Yi WuMing-Hsuan Yang

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Software Mentioned

RDTracks
Dynamic
Twins
WiSee
LiFS
Rollcaller
RDTrack
Pilot
MUSIC
ACE

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