Digital Signal Processing

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Indoor RFID Tracking System Based on UKF Fusion Estimation Techniques


Affiliations
1 Department of Electronics and Telecommunication Engineering, Jabalpur Engineering College (JEC), Jabalpur, Madhya Pradesh, 482011, India
     

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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.

Keywords

Adaptive Filtering, Augmented UKF, RFID Indoor Tracking, RFID Measurement Data, RSSI.
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  • Indoor RFID Tracking System Based on UKF Fusion Estimation Techniques

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Authors

Jitendra Damade
Department of Electronics and Telecommunication Engineering, Jabalpur Engineering College (JEC), Jabalpur, Madhya Pradesh, 482011, India
Agya Mishra
Department of Electronics and Telecommunication Engineering, Jabalpur Engineering College (JEC), Jabalpur, Madhya Pradesh, 482011, India

Abstract


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.

Keywords


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

References