Three Dimensional Fuzzy Logic Based-Map Matching Algorithm for Location Based Service Applications in Urban Canyons

A major portion of the Location-Based Services (LBS) market deals with applications involving in-car navigation systems. Many such LBS applications involve positioning in urban areas which contain high rise buildings. The Global Positioning System (GPS) is the most popular choice for navigating vehicles, primarily due to its autonomous positioning ability. Although GPS has good positioning accuracy in open sky conditions, it suffers from line-of-sight issues in downtown areas with urban canyons. This reduces effectiveness as the satellite availability is degraded. The other major problem associated with positioning in urban canyons is the multipath error arising from reflections off buildings. The availability can be improved by using a High Sensitivity GPS (HS GPS) receiver which can acquire and track weak signals. However, weak signal tracking may introduce large errors and noise in measurements. Thus, integrity monitoring is necessary with such receivers in signal degraded environments. This monitoring is effective if constraints can be imposed on the position parameters. In this paper a height-aided map matching algorithm is proposed to improve vehicle navigation in urban canyons. The input to the system comes from a low cost gyro (Murata ENV-05), a HS GPS receiver, a map database and a Digital Elevation Model (DEM). The information from the map and DEM are used as constraints in outlier detection and for enhanced position computation. A comparison is done between the results obtained by the proposed algorithm and two dimensional map matching approaches. The results show an improvement of more than 25% in the computation of an optimal navigation solution.