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Efficient Object Localisation Using Sparsely Distributed Passive RFID Tags

YANG, Po, WU, Wenyan, MONIRI, Mansour and Chibelushi, C.C. (2013) Efficient Object Localisation Using Sparsely Distributed Passive RFID Tags. IEEE Transactions on Industrial Electronics, 60 (12). pp. 5914-5924. ISSN 0278-0046 (In Press)

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Abstract or description

Radio-Frequency Identification (RFID) technology has been widely used in passive RFID localisation application due to its flexible deployment and low-cost. But current passive RFID localisation systems cannot achieve both highly accurate and precise moving object localisation task owing to tag collisions and variation of the behavior of tags. Most researchers increase the density of tag distribution to improve localisation accuracy, and then consider using either anti-collision process embedded in the hardware of the RFID reader or advanced localisation algorithms to enhance localisation precision. However, advanced anti-collision processes for RFID devices are challenged by the physical constraint characteristics of radio frequency; and improved localisation algorithm cannot fundamentally reduce the impacts of tag collision on localisation precision. This research work attempts to improve localisation precision of a passive RFID localisation system by using sparsely distributed RFID tags. This paper first defines a measure for accuracy and precision in a passive RFID localisation system with regard to RFID Tag Distribution. An exponential based function is then derived from experimental measurements, which reflects the relationship between RFID Tag Distribution and localisation precision. This function shows that localisation precision is mainly determined by tag density of RFID Tag Distribution. Based on the experimental findings, a sparse RFID Tag Distribution approach is proposed. The results show that in comparison with the conventional RFID Tag Distribution; passive RFID localisation system with sparse RFID Tag Distribution can deliver a higher localisation precision for the required accuracy.

Item Type: Article
Faculty: Previous Faculty of Computing, Engineering and Sciences > Computing
Depositing User: Claude CHIBELUSHI
Date Deposited: 10 Apr 2013 19:19
Last Modified: 24 Feb 2023 13:37

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