An adaptive location estimator using tracking algorithms for indoor WLANs

• Published in: Wireless networks 2010-10, Vol.16 (7), p.1987-2012
• Main Authors: Chiou, Yih-Shyh, Wang, Chin-Liang, Yeh, Sheng-Cheng
• Format: Article
• Language: English
• Subjects: Accuracy; Adaptive algorithms; Algorithms; Communications Engineering; Computer Communication Networks; Electrical Engineering; Engineering; Global positioning systems; GPS; Indoor; Infrastructure; International; IT in Business; Local area networks; Mathematical models; Methods; Network management systems; Networks; Noise; Position (location); Probability distribution; Propagation; Radio communications; Radio frequency; Radio frequency identification; Sensors; Studies; Wireless communication; Wireless networks
• ISSN: 1022-0038; 1572-8196
• DOI: 10.1007/s11276-010-0240-8

This paper presents adaptive algorithms for estimating the location of a mobile terminal (MT) based on radio propagation modeling (RPM), Kalman filtering (KF), and radio-frequency identification (RFID) assisting for indoor wireless local area networks (WLANs). The location of the MT of the extended KF positioning algorithm is extracted from the constant-speed trajectory and the radio propagation model. The observation information of the KF tracker is extracted from the empirical and RPM positioning methods. Specifically, a sensor-assisted method employs an RFID system to adapt the sequential selection cluster algorithm. As compared with the empirical method, not only can the RPM algorithm reduce the number of training data points and perform on-line calibration in the signal space, but the RPM and KF algorithms can alleviate the problem of aliasing. In addition, the KF tracker with the RFID-assisted scheme can calibrate the location estimation and improve the corner effect. Experimental results demonstrate that the proposed location-tracking algorithm using KF with the RFID-assisted scheme can achieve a high degree of location accuracy (i.e., more than 90% of the estimated positions have error distances of less than 2.1 m).