Title :
Artificial Neural Networks for ranging of passive UHF RFID tags
Author :
Agatonovic, Marija ; Di Giampaolo, Emidio ; Tognolatti, Piero ; Milovanovic, Bratislav
Author_Institution :
Fac. of Electron. Eng., Univ. of Nis, Nis, Serbia
Abstract :
Ranging of passive Ultra High Frequency (UHF) Radio Frequency Identification (RFID) tags in indoor environments is a topical issue nowadays. Due to complexity of such an environment, there is no effective solution to this problem. In this paper we investigate application of Artificial Neural Networks (ANNs) in indoor localization of passive UHF RFID tags. Namely, we estimate distance between a reader antenna and a couple of tags attached to an item, using nonlinear mapping that ANNs perform between measured values of the Received Signal Strength Indicator (RSSI), turn on power and phase on the one hand, and the distance on the other. The proposed ANN model calculates distance with an average error of 7.31 cm.
Keywords :
UHF antennas; indoor radio; neural nets; radiofrequency identification; radionavigation; telecommunication computing; ANN model; RSSI; artificial neural networks; distance estimation; indoor environments; indoor localization; nonlinear mapping; passive UHF RFID tag ranging; passive UHF RFID tags; passive ultra high frequency; radio frequency identification tags; reader antenna; received signal strength indicator; Antenna measurements; Artificial neural networks; Distance measurement; Passive RFID tags; Phase measurement; Training; ANNs; RFID; passive UHF RFID tags;
Conference_Titel :
Telecommunication in Modern Satellite, Cable and Broadcasting Services (TELSIKS), 2013 11th International Conference on
Conference_Location :
Nis
Print_ISBN :
978-1-4799-0899-8
DOI :
10.1109/TELSKS.2013.6704428
