Improving the Prediction of GNSS Satellite Visibility in Urban Canyons Based on a Graph Transformer
Signals from global navigation satellite systems (GNSSs) in urban areas suffer from serious multipath errors caused by building blockages and reflections.The use of deep neural networks offers great potential for predicting and eliminating complex multipath/non-line-of-sight (NLOS) errors.However, existing methods for predicting the original signal