Adapted Robust GNSS RTK Positioning

The need for high-accuracy and high-integrity positioning using global navigation satellite system (GNSS) sensors is increasing, given that GNSSs are the only observation systems capable of delivering absolute positioning information. Nevertheless, all GNSS positioning techniques are susceptible to environmental conditions, presenting a significant challenge in meeting the localization requirements for autonomous vehicles, especially in dense urban environments. This paper presents a novel approach that combines map information with robust estimation techniques to provide high-accuracy and high-integrity localization of vehicles – even in dense urban environments. The proposed adapted robust GNSS real-time kinematic positioning method includes a newly developed robust estimator – the HG-estimator – that retains the advantages of existing robust loss functions and mitigates their drawbacks. This strategy was evaluated and validated through two kinematic automotive experiments situated within medium and deep urban trenches. The application of the HG-estimator incorporating map information resulted in improvements of 54 % and 60 % in horizontal accuracy compared with a C/N₀ weight model for the medium and deep urban trenches, respectively. Consequently, lane-keeping and lane determination accuracy requirements were met.