GNSS obstacle mapping as a data preprocessing tool for positioning in a multipath environment

Abstract

The presence of terrain obstacles, for instance in urban, mountain or forest environments, significantly affects the accuracy of global navigation satellite system (GNSS) measurements, due to signal reception blockage and the multipath effect. The multipath remains a domain source of ranging errors in satellite positioning. When considering a session of a few hours, this type of error cannot be eliminated by differential techniques because its influence is uncorrelated with time and space. In order to minimize the influence of multipath, various methods can be applied. We present a data preprocessing tool for GPS multipath detection and mitigation based on GNSS obstacle mapping. Because reception of non-line-of-sight signals is closely connected with the place of observation, the maps of obstacles derived from on-point hemispherical images were applied. The main assumption of the proposed method is to remove from observations those received from satellites, which according to the map were behind the obstacle. As a reference two data sets were used. The first one was a set of unfiltered observations. In the second data set used for comparison there were measurements for which the C/N 0 value was greater than 40 dB Hz-1. The research showed that if the data registered from obstructed signals is deleted, the positioning accuracy will be better, despite the decreasing visible satellites number and the dilution of precision coefficient devaluation.