DocumentCode :
1642408
Title :
An Adaptive Location Estimator Based on Kalman Filtering for Dynamic Indoor Environments
Author :
Chiou, Yih-Shyh ; Wang, Chin-Liang ; Yeh, Sheng-Cheng
Author_Institution :
Inst. of Commun. Eng., Nat. Tsing Hua Univ., Hsinchu
fYear :
2006
Firstpage :
1
Lastpage :
5
Abstract :
This paper presents algorithms for calibrating and tracking the location of a mobile terminal based on radio propagation modeling (RPM) and Kalman filtering for indoor wireless local area networks (WLANs). In this Kalman filter-based (KF-based) tracking algorithm, the observed location information is extracted from the empirical and RPM positioning methods. Not only can the proposed RPM algorithm calibrate the change of different environmental conditions in a real dynamic environment but also the KF-based tracking algorithm can reduce the location error with smaller sampling time and vanquish the phenomenon of the aliasing in the signal space. Our experimental results show that more than 90 percent of the estimated locations have error distances less than 2.3 meters.
Keywords :
Kalman filters; adaptive estimation; error statistics; indoor radio; mobile computing; mobile radio; radio tracking; radiowave propagation; signal sampling; wireless LAN; Kalman filter-based tracking algorithm; adaptive location estimation; dynamic indoor wireless local area network environment; empirical positioning method; location error statistic; mobile terminal; radio propagation modeling; signal sampling; Adaptive filters; Data mining; Filtering algorithms; Indoor environments; Information filtering; Information filters; Kalman filters; Radio propagation; Sampling methods; Wireless LAN;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Vehicular Technology Conference, 2006. VTC-2006 Fall. 2006 IEEE 64th
Conference_Location :
Montreal, Que.
Print_ISBN :
1-4244-0062-7
Electronic_ISBN :
1-4244-0063-5
Type :
conf
DOI :
10.1109/VTCF.2006.585
Filename :
4109850
Link To Document :
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