Mapping Dilution of Precision (MDOP) and map-matched GPS

A novel method of map matching using the Global Positioning System (GPS) has been developed which uses digital mapping and height data to augment point position computation. This method reduces the error in position, which is a sum from several sources, including signal delay due to the ionosphere and atmosphere and until recently from ‘selective availability’ (S/A). S/A was imposed by the USmilitary to degrade purposefully the accuracy of GPS, but was switched oŒon 2 May 2000, and is to be replaced with ‘regional denial capabilities in lieu of global degradation’ (Interagency GPS Executive Board, 2000). Taylor et al. (2001) describe the Road Reduction Filter (RRF) in detail. RRF is a method of detecting the correct road on which a vehicle is travelling. In the work described here, the position error vector is estimated in a formal least squares procedure, as the vehicle is moving. This estimate is a map-matched correction, that provides an autonomous alternative to DGPS for in-car navigation and  eet management. In this paper, a formula is derived for ‘Mapped Dilution of Precision’ (MDOP), deŽ ned as the theoretical ratio of position precision using map-matched corrections to that using perfect DiŒerential GPS (DGPS) correction. This is shown to be purely a function of route geometry, and is computed for examples of basic road shapes. MDOP is favourable unless the route has less than a few degrees curvature for several kilometres. MDOP can thus provide an objective estimate of positioning precision to a vehicle driver. Precision estimates using MDOP are shown to agree well with ‘true’ positioning errors determined using high precision (cm) GPS carrier phase techniques. The exact location of a vehicle on a road is essential for accurate surveying applications. These include close range photogrammetry using digital video or still cameras and the veriŽ cation of digital mapping by measured (GPS and other sensors) trajectories.