The Project
Get to know what makes the impossible possible
The AGORA project aims at providing two machine learning-based correction algorithms which improve navigation solutions using GNSS only:
Agora Multipath
Multipath, which occurs when GNSS signals reflect off surfaces (e.g., buildings) before reaching the receiver, leads to inaccuracies in position estimates. ML algorithms can analyse signal characteristics and environmental factors to generate a correction to compensate for the multipath generated errors in positioning, enabling more accurate positioning even in challenging urban environments.
Agora Ionosphere
The ionosphere, through which the GNSS signals pass, can cause signal delays that vary with factors like time of day, location, and solar activity. Here, machine learning in GNSS technology relates to the prediction and compensation of ionospheric delays. ML algorithms can analyse historical data and real-time observations to model ionospheric behaviour and prediction, allowing GNSS receivers to apply corrections and improve positioning accuracy.