Trio: Utilizing Tag Interference for Refined Localization of Passive RFID

Ding, Han; Han, Jinsong; Qian, Chen; Xiao, Fu; Wang, Ge; Yang, Nan; Xi, Wei; Xiao, Jian

doi:10.1109/infocom.2018.8486313

Cited by 41 publications

(7 citation statements)

References 19 publications

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“…The antenna is moved along a straight-line trajectory which is shown by the blue line in Fig. 4.1 (1). The LiDAR trajectory is estimated from fixed boards which are placed at the edges of the area at a known location.…”

Section: Results With a Straight-line Trajectorymentioning

confidence: 99%

“…Over the past decade, passive Ultra High Frequency-Radio Frequency Identification (UHF-RFID) technology has attracted increasing interest due to its advantages such as contactless communication, multi-object recognition, and low-cost [1,2] and has become widely used in various scenarios such as inventory interrogation in warehouses, factories and stores [2,3]. Recently, there is an increasing requirement for accurate positional information of materials and products in an indoor environment where the Global Positioning System (GPS) is unable to reach and is too expensive [4,5].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An ISAR-SAR Based Method for Indoor Localization Using Passive UHF RFID System With Mobile Robotic Platform

Liu

et al. 2021

IEEE J. Radio Freq. Identif.

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A novel RFID inverse synthetic aperture radar (ISAR)-synthetic aperture radar (SAR) localization method is proposed and demonstrated which exploits reference tags with known locations to estimate the trajectory of a mobile platform and locate target tags with unknown locations. A system that integrates a mobile robot with an integrated RFID reader and antenna is used to obtain phase measurements of both reference and target tags when the robot is moving along its trajectory. The ISAR algorithm estimates the antenna trajectory and a novel ISAR-SAR loop then adjusts the estimated trajectory. The estimated trajectory is combined with phase measurements of the target tags to determine their location. The performance is compared to SAR using a LiDAR measured antenna trajectory. Similar localization accuracy (15 cm MAE) is achieved using LiDAR-SAR or ISAR-SAR method with a straight-line trajectory and higher accuracy (6 cm) is achieved using ISAR-SAR method than LiDAR-SAR method (8 cm) with an L-shape trajectory.

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Section: Results With a Straight-line Trajectorymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An ISAR-SAR Based Method for Indoor Localization Using Passive UHF RFID System With Mobile Robotic Platform

Liu

et al. 2021

IEEE J. Radio Freq. Identif.

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“…For RSS based methods, one of the representative techniques estimates the tag position by comparing the RSS from the target tag with reference tags [23]. Moreover, another technique can obtain the refined tag position by utilizing the characteristics of the coupling effect on RSS [24]. However, due to the low resolution of RSS, developing an RSS based localization scheme with high accuracy is challenging.…”

Section: Related Researchmentioning

confidence: 99%

Unsupervised Detection of Apnea Using Commodity RFID Tags With a Recurrent Variational Autoencoder

2019

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With the rapid development of intelligent health sensing in the Internet of Things (IoT), vital sign monitoring (e.g., respiration) and abnormal respiration detection have attracted increasing attention. Considering the challenging and the cost of collecting labeled training data from patients with breathing related diseases, we develop the AutoTag system, an unsupervised recurrent variational autoencoder-based method for respiration rate estimation and abnormal breathing detection with off-the-shelf RFID tags. Moreover, for real-time breath monitoring, a novel method is proposed to cancel the distortion on measured phase values caused by channel hopping for FCC-complaint RFID systems. The efficacy of the proposed system is demonstrated by the extensive experiments conducted in two indoor environments, while the impact of various design and environmental factors is also evaluated.INDEX TERMS Apnea, deep learning, radio-frequency identification (RFID), recurrent variational autoencoder, respiration monitoring.

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“…Mutual coupling of adjacent tags can result in the changes of RSS and phase [33]. In some extreme cases, the coupled tags will become inactive.…”

Section: Avoiding the Effect Of Mutual Couplingmentioning

confidence: 99%

Passive Multiple Target Indoor Localization Based on Joint Interference Cancellation in an RFID System

Li¹,

Ma²,

Wang³

et al. 2019

Electronics

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Radio frequency identification (RFID) provides a simple and effective solution to the passive indoor localization. The conventional wisdom about RFID localization is using reference tags. It performs well in tag or passive single target localization. However, in the passive multiple target scenario, reference tag based localization suffers from some limitations, including the array aperture, mutual coupling of reference tags, and coherent superimposition signals. These problems are harmless and ignored in tag or passive single target localization, but degrade the performance severely in passive multiple target scenario. Therefore, in this paper, the authors propose a joint interference cancellation method to mitigate the effect of these limitations. Uniform circular array (UCA) of reference tags were used to reduce the interference of the array aperture. A carefully designed relative position of adjacent reference tags and a modified channel model were combined to reduce the mutual coupling. A virtual distributed reader antenna array was used to reduce the false positive and false negative estimations. The system was evaluated in real indoor environment using noodles and colas as targets and can work well in a smoky environment that is similar to some real industrial environments. The accuracy of target number estimation is 97.5%. The spatial resolution is about 30 cm, and the median error of 2-D multiple target localization is about 5.5 cm.

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Trio: Utilizing Tag Interference for Refined Localization of Passive RFID

Cited by 41 publications

References 19 publications

An ISAR-SAR Based Method for Indoor Localization Using Passive UHF RFID System With Mobile Robotic Platform

An ISAR-SAR Based Method for Indoor Localization Using Passive UHF RFID System With Mobile Robotic Platform

Unsupervised Detection of Apnea Using Commodity RFID Tags With a Recurrent Variational Autoencoder

Passive Multiple Target Indoor Localization Based on Joint Interference Cancellation in an RFID System

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