Comparison of extended and Unscented Kalman Filter for localization of passive UHF RFID labels

Due to the increased use of Radio Frequency Identification (RFID) in different fields of application it is reasonable to explore the benefit that can be obtained by the simultaneous localization of RFID tags. This paper describes the localization of a passive UHF RFID tag via Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) using the Received Signal Strength Indicator (RSSI) values. Simulation results based on measurements show that UKF achieves higher localization accuracies than EKF.

[1]  Nak Young Chong,et al.  Automated Robot Docking Using Direction Sensing RFID , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[2]  Nol Premasathian,et al.  An improvement of an RFID indoor positioning system using one base station , 2009, 2009 6th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology.

[3]  Abdelmoula Bekkali,et al.  RFID Indoor Positioning Based on Probabilistic RFID Map and Kalman Filtering , 2007, Third IEEE International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob 2007).

[4]  Sebastian Thrun,et al.  Probabilistic robotics , 2002, CACM.

[5]  Lutz H.-J. Lampe,et al.  A comparison between Unscented Kalman Filtering and particle filtering for RSSI-based tracking , 2010, 2010 7th Workshop on Positioning, Navigation and Communication.

[6]  Yunhao Liu,et al.  LANDMARC: Indoor Location Sensing Using Active RFID , 2004, Proceedings of the First IEEE International Conference on Pervasive Computing and Communications, 2003. (PerCom 2003)..

[7]  Peter Gulden,et al.  An overview of wireless local positioning system configurations , 2009, 2009 IEEE MTT-S International Microwave Workshop on Wireless Sensing, Local Positioning, and RFID.

[8]  F. Martinelli.  Robot localization: comparable performance of EKF and UKF in some interesting indoor settings , 2008, 2008 16th Mediterranean Conference on Control and Automation.

[9]  M Ayoub Khan,et al.  Location Estimation Technique using Extended 3-D LANDMARC Algorithm for Passive RFID Tag , 2009, 2009 IEEE International Advance Computing Conference.

[10]  Samer S. Saab,et al.  A Standalone RFID Indoor Positioning System Using Passive Tags , 2011, IEEE Transactions on Industrial Electronics.