Simulating GNSS multipath in urban environments using 3D ray tracing for automotive applications

Accurate localization is essential for autonomous driving and Advanced Driver Assistance Systems (ADAS) to ensure safe and reliable vehicle navigation. In urban environments, multipath propagation is a major source of error in GNSS-based positioning, as signals reflect off buildings, structures, and other city elements, leading to degraded localization performance. This issue significantly impacts autonomous vehicles and ADAS applications, where precise positioning is critical for decision-making and safety. To address this challenge, we propose a method to simulate the multipath effect using a ray-tracing approach based on the 3D city model. The CARLA open-source simulator is used to recreate urban environments and vehicle trajectories, while an octree-based ray-tracing technique computes the possible signal reflections from GNSS satellites to vehicle positions. These signals are then used to estimate the amplitude and phase of both Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) components, allowing for the calculation of multipath-induced errors using standard Delay Lock Loop (DLL) mechanisms. Finally, raw pseudorange and carrier phase measurements are generated, incorporating the estimated multipath effects. The proposed model provides a more detailed simulation of multipath propagation and signal obstructions compared to existing methods. This is reflected in the increased positioning error observed in urban scenarios, particularly in areas with limited satellite visibility, such as under rail tracks. To promote open science and reproducibility, we also share the dataset obtained with this simulation pipeline, containing the generated measurements as well as the results presented in this paper. This simulation approach has broad applications, including the development of enhanced localization algorithms for ADAS and autonomous vehicles, multipath mitigation techniques, sensor fusion strategies, and Artificial Intelligence-driven positioning systems. • Simulation framework for GNSS multipath using CARLA and raw sensor data. • Ray tracing to model multipath in dynamic urban driving scenarios. • Multipath interference modelling for accurate signal power, delay, and phase. • Flexible, low-cost GNSS multipath simulation for urban vehicle testing. • Public dataset with GNSS, IMU, and ground truth from 3D urban simulations.