Work

Predicting GNSS satellite visibility from dense point clouds

Year: 2019
Type: preprint
Abstract: 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 environments
Institution: Université Laval
Language: English
Open Access status: green
OpenAlex ID: W2941933124
Cites: 15
Cited by:
Related to: 20