A HYBRID APPROACH TO GPS IMPROVEMENT IN URBAN CANYONS

GPS has become important tool in everyday life for safe and convenient transportation of automobiles. Pedestrians use hand held smart devices to know their own position in a town, modern vehicles in intelligent transport systems use relatively sophisticated GPS receivers for estimating current position of vehicle for safe driving. However, in urban areas with canyon of buildings where the GPS satellites are occluded by tall buildings, trees and reflections of GPS signals from nearby vehicles, GPS position estimation becomes poor. In this paper, a hybrid approach to improve GPS data is presented. GPS data is captured at a single point in urban area around which many tall buildings are present. The data is taken under different times of day so that satellites positions are changed and under dynamic environmental conditions so that occlusions are changed.. The data is processed and analyzed using statistical methods. The improvement methods are used to obtain an optimal position estimate among all the measured data points. The improvement results are compared with many publically available datasets. The obtained position estimation improvement made with the hybrid approach are promising