Variable Number of Multi-Sensor Fusion for Indoor RFID Tracking System

Article Preview

Abstract:

We present a new method to accurately tracking persons indoors by active RFID technology. To deal with nonlinear measurement model, the EKF(extended Kalman filter) is used to estimate the target trajectory. This paper developed the fusion estimation algorithm for the common indoor tracking problem with the reader at any location and fusion estimation with variable number of multi-sensor system. Simulations show the algorithm developed here can adaptively adjust the model parameter while tracking and obtain good estimation performance for indoor RFID tracking.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

654-657

Citation:

Online since:

August 2013

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Samer S. Saab, Zahi S. Nakad, A standalone RFID indoor positioning system using passive tags, IEEE Transactions on Industrial ElectronicS, Vol. 58(2011), pp.1691-1670.

DOI: 10.1109/tie.2010.2055774

Google Scholar

[2] H. H. Zhang, M. V. Basin, and M. Skliar, Ito-Volterra optimal state estimation with continuous, multirate, randomly sampled, and delayed measurements. IEEE Transactions on Automatic Control, Vol. 52(2007), pp.401-416.

DOI: 10.1109/tac.2007.892383

Google Scholar

[3] JIN Xue-bo, DU Jing-jing, BAO Jia, Target tracking of linear-time-invariant system under irregular sampling, International Journal of Advanced Robotic Systems, Vol. 9 (2012), pp.1-12.

DOI: 10.5772/54471

Google Scholar

[4] Li X R., Jilkov V P Survey of maneuvering target tracking 1: dynamic models. IEEE Transactions on Aerospace and Electronic Systems, Vol. 39 (2003), pp.1333-1364.

DOI: 10.1109/taes.2003.1261132

Google Scholar

[5] Xue-bo Jin, Jingjing Du, and Jia Bao, Data-Driven Tracking Based on Kalman Filter, Applied Mechanics and Materials, Vol. 226-228 (2012), pp.2476-2479.

DOI: 10.4028/www.scientific.net/amm.226-228.2476

Google Scholar