3D building model-assisted snapshot positioning algorithm

Abstract

A method for constructively using non-line-of-sight GNSS signals from a snapshot of signal samples for positioning of users in urban areas is presented here. Using a 3D building model and a ray-tracing algorithm, the number of reception paths and the corresponding path delays of reflected signals are predicted, across a rid of candidate positions. These predictions are then used to compute a least squares fit to the GNSS receiver’s correlator outputs, and the position with smallest residuals is selected as the position estimate. Using data collected along 3.5 km of road in downtown Calgary, Canada, where buildings reach heights of over 200 m, the root-mean-square position error is below 10 m in the along-track and across-track directions. Compared to two pseudorange-based receivers, the proposed method yields RMS error improvements of at least 31% in the along-track direction, 63% in the across-track direction, and 53% in the horizontal plane.