An Integrated WLAN and GPS Localization for Urban Canyon Environments using Sparse Data Processing

Ali Khalajmehrabadi, Nikolaos Gatsis, and David Akopian

Abstract:	This paper proposes a novel localization system for urban canyon environments through the marriage of Wireless Local Area Networks (WLAN) and the Global Positioning System (GPS). In the proposed technique, the wireless device receives GPS and WLAN signals simultaneously. If the GPS signals are sufficient for positioning, an Extended Kalman Filter (EKF) is used to provide a coarse location of the user. Otherwise, WLAN signals are used for coarse localization. Then, Access Points (APs) are selected for fine localization based on Fisher criterion. To obtain the fine location of the user, a Sparse Kalman Filter (SKF) is applied on the received online measurement and recorded WLAN radio map. The proposed method has been implemented on a real wireless device and the results show that the localization error has been reduced to 5 meters.
Published in:	Proceedings of the 30th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2017) September 25 - 29, 2017 Oregon Convention Center Portland, Oregon
Pages:	417 - 426
Cite this article:	Khalajmehrabadi, Ali, Gatsis, Nikolaos, Akopian, David, "An Integrated WLAN and GPS Localization for Urban Canyon Environments using Sparse Data Processing," Proceedings of the 30th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2017), Portland, Oregon, September 2017, pp. 417-426. https://doi.org/10.33012/2017.15198
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