Passive UHF-RFID Localization Based on the Similarity Measurement of Virtual Reference Tags

• Published in: IEEE transactions on instrumentation and measurement Vol. 68; no. 8; pp. 2926 - 2933
• Main Authors: Mo, Lingfei, Li, Chenyang
• Format: Journal Article
• Language: English
• Published: New York IEEE 01-08-2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Antenna measurements; Indoor localization; Industrial applications; Interpolation; Laiyite criterion; Localization; Mathematical analysis; Mathematical model; Measurement uncertainty; Multilayer perceptrons; multipath error; natural neighbor interpolation (NNI); Neural networks; phase; Phase measurement; Position indicators; Radio frequency identification; Radiofrequency identification; Signal strength; Similarity; Supermarkets; Tags; Ultrahigh frequencies; ultrahigh frequency radio frequency identification (UHF-RFID); Very high frequencies
• ISSN: 0018-9456; 1557-9662
• DOI: 10.1109/TIM.2018.2869408

With the appearance of the new concepts "smarter planet," "industry 4.0" and "self-service supermarket," radio frequency identification (RFID), a key technology of Internet of Things, has been a hot research topic in recent years. Owing to the long read range, fast read speed and low cost, RFID in the ultrahigh frequency using passive tags has achieved great development in the management and tracking of asset and warehousing, personnel location, and robot navigation. In the meantime, there is a growing demand for the accurate localization indoors. In this paper, a method of similarity measurement of virtual reference tags using phase and receive signal strength indicator (RSSI) is designed to estimate the position of tags. The attributes of virtual reference tags, such as phase and RSSI, are calculated by the natural neighbor interpolation. Moreover, the Laiyite criterion with variable coefficient is presented to remove the multipath error. A 2-D platform is deployed to test the validity of the method. Compared with a k-nearest neighbor and multilayer perceptron, similarity measurement of virtual reference tags has a better performance for localization, which can meet the demand of the practical application.