A Map-Matching Based Approach to Compute and Modelize NLOS and Multipath Errors for GNSS Positioning in Hard Areas

In Global Navigation Satellite systems (GNSS), the performances of classical localization methods show a significant degradation in constrained environments (urban and indoor environments), due to Non-Line-of-Sight(NLOS) and Multipath phenomena affecting GNSS signal. In order to improve positioning accuracy in hard environment, this paper aims to propose an approach to compute and adapt the NLOS and Multipath error model to GNSS signal reception conditions. The approach aims firstly to propose a Map-Matching based-technique to compute Multipath and NLOS errors in real time positioning, secondly, to test adequacy of these errors with the most used models in the literature and finally to model the Multipath and NLOS errors using Gaussian mixture noise. As a result, we have shown that a Gaussian, Rayleigh and Uniform model were not be able to model effectively Multipath and NLOS errors and we have demonstrated that a Gaussian mixture model can approximate these errors and improve positioning accuracy in urban environment.