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Indoor RFID Tracking System Based on UKF Fusion Estimation Techniques

Jitendra Damade, Dr. Agya Mishra


Radio Frequency Identification (RFID) is very popular and effective technology in the field of security and identification. In indoor RFID tracking system, the distance measured between the RFID reader and the tag is collected from the received signal strength indicator (RSSI). Due to multivariate, irregularly sampled, uncertain, and nonlinear of the measurements and limit of the deployment of readers, an efficient estimation method is involved to acquire the accurate trajectory in indoor RFID tracking system. In this paper, features of RFID reader measurement mechanism are analyzed, an RFID measurement system model is proposed, and the Unscented Kalman Filter (UKF)-based fusion estimation algorithm is proposed for real trajectory tracking. UKF have an ability to deal with nonlinearity of the system and adaptive to the uncertainty of the RFID measurement data. This paper concludes with experimental analysis of performance of the proposed system model. Results show that this model can be implemented efficiently in the field of trajectory tracking and personal identification system.


Adaptive Filtering, Augmented UKF, RFID Indoor Tracking, RFID Measurement Data, RSSI.

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