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RFID Tag Localization With a Sparse Tag Array

Chao Yang, Xuyu Wang, Shiwen Mao

2021IEEE Internet of Things Journal22 citationsDOI

Abstract

With the rapid growth of the Internet of Things (IoT), the radio-frequency identification (RFID) technology has been recognized as an effective and low-cost solution for many IoT applications. In this article, we study the problem of utilizing a sparse RFID tag array for backscatter indoor localization. We first theoretically and experimentally validate the feasibility of using sparse tag arrays for the direction of arrival (DOA) estimation. We then present the SparseTag system, which leverages a novel sparse tag array for high-precision backscatter indoor localization. The SparseTag system includes sparse array processing, difference co-array design, DOA estimation using a spatial smoothing-based method, and a localization method. A robust channel selection method based on the RFID tag array is adopted for mitigating the multipath effect. The SparseTag system is implemented with commodity RFID devices. Its superior performance is validated in two different environments with extensive experiments and comparison to baseline schemes.

Topics & Concepts

Computer scienceSparse arrayMultipath propagationSmoothingSensor arrayChannel (broadcasting)Real-time computingBackscatter (email)Radio-frequency identificationWirelessTelecommunicationsAlgorithmComputer visionComputer securityMachine learningIndoor and Outdoor Localization TechnologiesDirection-of-Arrival Estimation TechniquesSpeech and Audio Processing
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