Location Based on Passive RFID by Using Least Squares SVM

In this paper, two location algorithms are mentioned. One is LANDMARC, which has a good performance of anti-interference, but it is an approximate estimate and cannot get an accurate result. It heavily depends on the empirical formula and the layout of reference tags. The other algorithm proposed in this paper is the location algorithm based on least squares SVM. It uses the least squares SVM to get the mapping of RSSI to distance, and then gets the position results by using least-squares method. According to the simulation, it has a better performance comparing to LANDMRC.

[2]  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)..

[3]  Johan A. K. Suykens,et al.  Least Squares Support Vector Machine Classifiers , 1999, Neural Processing Letters.

[4]  Ramez Elmasri,et al.  Passive UHF RFID-Based Localization Using Detection of Tag Interference on Smart Shelf , 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[5]  Paramvir Bahl,et al.  RADAR: an in-building RF-based user location and tracking system , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[6]  Weimin Zhang,et al.  LSSVM Parameters Optimizing and Non-linear System Prediction Based on Cross Validation , 2009, 2009 Fifth International Conference on Natural Computation.

[7]  Vladimir Vapnik,et al.  Statistical learning theory , 1998 .

[8]  Martin Slanina,et al.  Indoor channel modeling based on experience with outdoor urban measurement — Multislope modeling , 2011, 2011 IEEE International Conference on Microwaves, Communications, Antennas and Electronic Systems (COMCAS 2011).

[9]  Ye Xu,et al.  The Research and Design of the Indoor Location System Based on RFID , 2011, 2011 Fourth International Symposium on Computational Intelligence and Design.

[10]  Gaetano Borriello,et al.  SpotON: An Indoor 3D Location Sensing Technology Based on RF Signal Strength , 2000 .