3-Dimensional Reconstruction on Tagged Packages via RFID Systems

Bu, Yanling; Xie, Lihua; Liu, Jia; He, Bingwei; Gong, Yinyin; Lu, Sanglu

doi:10.1109/sahcn.2017.7964911

Cited by 18 publications

(2 citation statements)

References 19 publications

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“…Moreover, benefitting from the low cost of the RFID tag, the tag array has a lower cost contrasted with the antenna array [12,13]. In recent years, tag arrays have been widely used in 3D reconstruction [14], gesture recognition [15], and human motion sensing [16,17]. Besides, tag array is also a great choice for indoor localization systems.…”

Section: Introductionmentioning

confidence: 99%

An AOA and Orientation Angle-Based Localization Algorithm for Passive RFID Tag Array

Xie

Ren

Wang

et al. 2022

Wireless Communications and Mobile Computing

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This paper proposes an indoor localization algorithm based on AOA (Arrive of Angle) and orientation angle (OA) for passive UHF RFID (Ultra-High Frequency Radio Frequency Identification) tag array. By utilizing a uniform linear tag array (ULA), the AOA, which is defined as the angle of the reader relative to the tag array, can be estimated by the Multiple Signal Classification (MUSIC) algorithm. The relationship between AOA, OA of the tag array, and the direction angle (DA) between each reader antenna to the geometric center of the tag array is analyzed, and an OA retrieval method based on rotating the coordinate system is proposed to calculate DA. The tag array localization is finally acquired by the DA of each antenna. Simulation and experiment results show that the proposed algorithm can achieve decimeter-level localization accuracy. The proposed algorithm achieves a mean accuracy of 0.216 m, which is a significant improvement compared with the traditional AOA localization algorithm.

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Section: Introductionmentioning

confidence: 99%

An AOA and Orientation Angle-Based Localization Algorithm for Passive RFID Tag Array

Xie

Ren

Wang

et al. 2022

Wireless Communications and Mobile Computing

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“…Recently, RFID technology was used in 3D reconstruction. For example, Bu et al presented a new theory based on the phase difference of RFID tags for 3D reconstruction of standard cubes [30]. Most existing RFID-based 3D reconstruction methods adopt an architecture of finding optimized results among multiple potential poses [30]- [32], which limits their applicability for UAV indoor localization, where six degrees of freedom (6-DoF) poses are needed in real-time.…”

Section: Introductionmentioning

confidence: 99%

Robust RFID Based 6-DoF Localization for Unmanned Aerial Vehicles

Zhang

Wang

et al. 2019

IEEE Access

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Although Unmanned Aerial Vehicles (UAV) are usually deploy outdoors, there is increasing interest in applying UAVs for indoor applications. It is a highly attractive and challenging task to precisely localize a UAV in an indoor environment where Global Positioning System (GPS) service is absent. In this paper, we present RFUAV, a Radio-frequency Identification (RFID) enhanced UAV system that provides a precise 6 degrees of freedom (6-DoF) pose for UAVs. With RFUAV, three or more ultra high frequency (UHF) RFID tags are attached to the UAV and are interrogated by a Commercial Off-The-Shelf (COTS) RFID reader with multiple antennas. Based on phase measurements of the RFID tag responses, the RFID tracker of RFUAV, a Bayesian filter-based algorithm, was employed to track the position of the tags in a global coordinate system. The pose estimator of RFUAV computes the 6-DoF pose of the UAV from tag positions. We tested the performance of RFUAV in a representative, structure-rich, indoor environment, where 0.04 m position error and 2.5 degrees orientation error were achieved. INDEX TERMS Radio-frequency identification (RFID), six degrees of freedom (6-DoF), indoor localization, unmanned aerial vehicle (UAV).

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Passive frequency comb generation at radiofrequency for ranging applications

Hussein,

Kim,

Rinaldi

et al. 2024

Nat Commun

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Optical frequency combs, featuring evenly spaced spectral lines, have been extensively studied and applied to metrology, signal processing, and sensing. Recently, frequency comb generation has been also extended to MHz frequencies by harnessing nonlinearities in microelectromechanical membranes. However, the generation of frequency combs at radio frequencies (RF) has been less explored, together with their potential application in wireless technologies. In this work, we demonstrate an RF system able to wirelessly and passively generate frequency combs. This circuit, which we name quasi-harmonic tag (qHT), offers a battery-free solution for far-field ranging of unmanned vehicles (UVs) in GPS-denied settings, and it enables a strong immunity to multipath interference, providing better accuracy than other RF approaches to far-field ranging. Here, we discuss the principle of operation, design, implementation, and performance of qHTs used to remotely measure the azimuthal distance of a UV flying in an uncontrolled electromagnetic environment. We show that qHTs can wirelessly generate frequency combs with μWatt-levels of incident power by leveraging the nonlinear interaction between an RF parametric oscillator and a high quality factor piezoelectric microacoustic resonator. Our technique for frequency comb generation opens new avenues for a wide range of RF applications beyond ranging, including timing, computing and sensing.

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3-Dimensional Reconstruction on Tagged Packages via RFID Systems

Cited by 18 publications

References 19 publications

An AOA and Orientation Angle-Based Localization Algorithm for Passive RFID Tag Array

An AOA and Orientation Angle-Based Localization Algorithm for Passive RFID Tag Array

Robust RFID Based 6-DoF Localization for Unmanned Aerial Vehicles

Passive frequency comb generation at radiofrequency for ranging applications

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