Efficient Particle Filter Localization Algorithm in Dense Passive RFID Tag Environment

Yang, Po and Wu, Wenyan (2014) Efficient Particle Filter Localization Algorithm in Dense Passive RFID Tag Environment. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 61 (10). pp. 5641-5651. ISSN 0278-0046

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Abstract

The means of distributing dense passive radiofrequency
identification (RFID) tags has been widely utilized for
accurate indoor localization. However, they suffer a disadvantage on low localization precision due to the increasing interference of RFID tag collisions and the variation of behavior of tags. Current localization algorithms used in passive RFID location systems are
mostly deterministic and have a limited capability on improving localization precision in a dynamic environment with uncertain sensor measurement. This paper investigates the feasibility of using particle filter technique as an efficient localization approach to deliver both relatively good accuracy and precision in dense passive
RFID tag distribution applications. A position feature-based
system model is first built to apply the typical particle filter technique in passive RFID location applications. Then, a new particle filter algorithm by using a moving direction estimation-based feature improvement scheme is proposed to enhance localization precision in a dense passive RFID tag environment. Experimental
results show that the proposed method can provide relatively good accuracy and precision for passive RFID location applications, with an improved performance over the typical particle filter algorithm and a state-of-the-art deterministic method.

Item Type: Article
Additional Information: (c) 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
Uncontrolled Keywords: Object localization, particle filter, radiofrequency identification (RFID).
Subjects: H100 General Engineering
Divisions: Faculty of Computing, Engineering and the Built Environment
Faculty of Computing, Engineering and the Built Environment > School of Engineering and the Built Environment
Faculty of Computing, Engineering and the Built Environment > School of Engineering and the Built Environment > Advanced Systems Engineering
UoA Collections > UoA15: General Engineering
Depositing User: Professor Wenyan Wu
Date Deposited: 04 Jan 2017 12:11
Last Modified: 01 Nov 2017 15:33
URI: http://www.open-access.bcu.ac.uk/id/eprint/3750

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