DocumentCode :
3659324
Title :
Hybrid technique for indoor positioning system based on Wi-Fi received signal strength indication
Author :
Peerapong Torteeka;Xiu Chundi;Yang Dongkai
Author_Institution :
Master Program of Space Technology and Application, School of Electronic and Information Engineering, Beihang University, Beijing, P.R. China
fYear :
2014
Firstpage :
48
Lastpage :
57
Abstract :
An indoor positioning system based on Receive Signal Strength Indication(RSSI) from wireless access equipment has become very popular in recent years. This system is very useful in many applications such as tracking service for older people or customer inside living communities, mobile robot localization, logistics systems etc. While outdoor environment using Global Navigation Satellite System(GNSS) and cellular network work well and are widespread used for navigation. However, there is a problem with signal propagation from satellites or cell site. They cannot be used effectively inside complex building areas or even in an urban environment. In general, the widely used method for indoor environment positioning based on Wi-Fi consists with two main categories, which are trilateration technique and location fingerprint technique(LF). It is already known that the explicit positioning performance of trilateration technique is more sensitive to noise effect than LF technique. Nevertheless, the accuracy of LF technique depends on training data set and it does not work well when environment changes. In this article, we propose the hybrid algorithm, the combination of the advantages of both systems, which is able to improve the accuracy stability and robustness. The performance of this algorithm is evaluated by the experimental results, which shows that our proposed scheme can achieve a certain level of positioning system accuracy.
Keywords :
"IEEE 802.11 Standard","Noise","Accuracy","Mathematical model","Training","Euclidean distance","Least squares approximations"
Publisher :
ieee
Conference_Titel :
Indoor Positioning and Indoor Navigation (IPIN), 2014 International Conference on
Type :
conf
DOI :
10.1109/IPIN.2014.7275467
Filename :
7275467
Link To Document :
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