Analysis of real-time GNSS positioning using NRTK corrections from Veneto Region and Hexagon networks

This master’s thesis evaluates the performance of real-time GNSS positioning using two Network RTK (NRTK) services: the Hexagon SmartNet GNSS RTK network and the Veneto Region GNSS RTK network. With the growing demand for high-precision positioning in sectors such as surveying, construction, and autonomous navigation, RTK has become an essential technique. However, its reliability is strongly influenced by environmental conditions, satellite geometry, and the configuration of reference station networks—particularly in areas with complex terrain or urban obstructions, such as the Veneto region. The study compares the accuracy and consistency of the two networks by collecting positioning data at two sites in Padova. Traditional topographic methods, including total station surveys and geometric levelling, were employed to establish precise reference points. Results show that Hexagon SmartNet GNSS RTK network generally offers superior stability and consistency, with lower median values and fewer outliers across Coordinate Quality (CQ) metrics (CQ1D, CQ2D, CQ3D) and Geometric Dilution of Precision (GDOP). While the Veneto Region GNSS RTK network delivered acceptable performance, it exhibited greater variability and occasional extreme deviations—particularly during early epochs and under challenging satellite geometry conditions. Interestingly, for distance and elevation differences, the Veneto Region GNSS RTK network outperformed Hexagon SmartNet GNSS RTK network, achieving its best distance precision at 360 seconds and best elevation precision at 6 seconds. In contrast, Hexagon SmartNet GNSS RTK network reached its minimum distance error at 5 seconds and minimum elevation error at 40 seconds. These findings suggest that the Veneto Region GNSS RTK network can offer superior precision in specific aspects, though not always with optimal time efficiency. An optimal observation time of 7 seconds was identified as the best compromise between precision and temporal efficiency, based on scalarization methods (L1, L2, and L∞ norms). In conclusion, Hexagon SmartNet GNSS RTK network emerged as the more consistent and reliable network for applications requiring stable performance, while the Veneto Region GNSS RTK network represents a robust alternative—particularly when vertical accuracy is prioritized. Financial considerations also play a role, as the Veneto Region GNSS RTK network is free of charge, whereas Hexagon SmartNet GNSS RTK network requires an annual subscription of approximately €500.