Title :
Fusion Estimation Based on UKF for Indoor RFID Tracking
Author_Institution :
Coll. of Comput. & Inf. Eng., Beijing Technol. & Bus. Univ., Beijing, China
Abstract :
Radio frequency identification (RFID) can effectively get the accurate location information for indoor tracking system. As to RFID sensor measurements with the multi-source and irregular sampling characteristics in the indoor tracking system, this paper gives the data-driven fusion estimation method based on Unscented Kalman filter (UKF). The experiments show that the fusion UKF can overcome RFID nonlinear better than EKF for indoor tracking application with RFID.
Keywords :
Kalman filters; indoor radio; radiofrequency identification; RFID sensor measurements; UKF; data-driven fusion estimation; indoor RFID tracking; indoor tracking system; location information; radio frequency identification; unscented Kalman filter; Acceleration; Estimation; Loss measurement; Noise; Radiofrequency identification; Target tracking; Trajectory; RFID; UKF; fusion estimation; indoor tracking;
Conference_Titel :
Green Computing and Communications (GreenCom), 2013 IEEE and Internet of Things (iThings/CPSCom), IEEE International Conference on and IEEE Cyber, Physical and Social Computing
Conference_Location :
Beijing
DOI :
10.1109/GreenCom-iThings-CPSCom.2013.358
