1 research outputs found
Predicting GNSS satellite visibility from dense point clouds
To help future mobile agents plan their movement in harsh environments,a
predictive model has been designed to determine what areas would be favorable
for Global Navigation Satellite System (GNSS) positioning. The model is able to
predict the number of viable satellites for a GNSS receiver, based on a 3D
point cloud map and a satellite constellation. Both occlusion and absorption
effects of the environment are considered. A rugged mobile platform was
designed to collect data in order to generate the point cloud maps. It was
deployed during the Canadian winter known for large amounts of snow and
extremely low temperatures. The test environments include a highly dense boreal
forest and a university campus with high buildings. The experiment results
indicate that the model performs well in both structured and unstructured
environment