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http://dx.doi.org/10.12815/kits.2020.19.1.94

Wireless LAN-based Vehicle Location Estimation in GPS Shading Environment  

Lee, Donghun (Graduate School of Automotive Engineering, Kookmin University)
Min, Kyungin (Graduate School of Automotive Engineering, Kookmin University)
Kim, Jungha (Department of Automobile and IT Convergence, Kookmin University)
Publication Information
The Journal of The Korea Institute of Intelligent Transport Systems / v.19, no.1, 2020 , pp. 94-106 More about this Journal
Abstract
Recently, the radio navigation method utilizing the GPS(Global Positioning System) satellite information is widely used as the method to measure the position of objects. As GPS applications become wider and fields based on various positioning information emerge, new methods for achieving higher accuracy are required. In the case of autonomous vehicles, the INS(Inertial Navigation System) using the IMU(Inertial Measurement Unit), and the DR(Dead Reckoning) algorithm using the in-vehicle sensor, are used for the purpose of preventing degradation of accuracy of the GPS and to measure the position in the shadow area. However, these positioning methods have many elements of problems due not only to the existence of various shaded areas such as building areas that are continually enlarged, tunnels, underground parking lots and but also to the limitations of accumulation-based location estimation methods that increase in error over time. In this paper, an efficient positioning method in a large underground parking space using Fingerprint method is proposed by placing the AP(Access Points) and directional antennas in the form of four anchors using WLAN, a popular means of wireless communication, for positioning the vehicle in the GPS shadow area. The proposed method is proved to be able to produce unchanged positioning results even in an environment where parked vehicles are moved as time passes.
Keywords
Indoor Localization; Wi-Fi Positioning System; Fingerprint Method;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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