DocumentCode :
3366509
Title :
Evaluation of WiFi-Based Indoor (WBI) Positioning Algorithm
Author :
Aboodi, Ahed ; Wan, Tat-Chee
Author_Institution :
Sch. of Comput. Sci., Univ. Sains Malaysia, Minden, Malaysia
fYear :
2012
fDate :
26-28 June 2012
Firstpage :
260
Lastpage :
264
Abstract :
This paper proposes an indoor positioning algorithm, WBI based on WiFi Received Signal Strength (RSS) technology in conjunction with trilateration techniques. The WBI algorithm estimates the location using RSS values previously collected from within the area of interest, determine whether it falls within the Min-Max bounding box, corrects for non-line-of-sight propagation effects on positioning errors using Kalman filtering, and finally update the location estimation using Least Square Estimation (LSE). The paper analyzes the complexity of the proposed algorithm and compares its performance against existing algorithms. Furthermore, the proposed WBI algorithm was able to achieve an average accuracy of 2.6 m.
Keywords :
Kalman filters; least squares approximations; minimax techniques; wireless LAN; Kalman filtering; RSS; WiFi based indoor positioning algorithm; least square estimation; location estimation; min-max bounding box; nonline-of-sight propagation effects; positioning errors; received signal strength technology; trilateration technique; Accuracy; Complexity theory; Estimation; Floors; Kalman filters; Least squares approximation; WBI; WiFi; indoor positioning; trilateration;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mobile, Ubiquitous, and Intelligent Computing (MUSIC), 2012 Third FTRA International Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
978-1-4673-1956-0
Type :
conf
DOI :
10.1109/MUSIC.2012.52
Filename :
6305859
Link To Document :
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