Open access
Aug 2026
Improving GNSS Performances in Location-Based Services through Synthetic Carrier-Phase Measurements
This work investigates whether machine learning, supported by precise satellite orbits and clocks, can predict carrier phase observations during signal gaps with millimeter-level accuracy and demonstrates that geometry-aware gap prediction is feasible at the sub-wavelength level.
P. Dabove, M. Bagheri, N. Gogoi
· The International Archives o... · 0 citations