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To help future mobile agents plan their movement in harsh environments,apredictive model has been designed to determine what areas would be favorablefor Global Navigation Satellite System (GNSS) positioning. The model is able topredict the number of viable satellites for a GNSS receiver, based on a 3Dpoint cloud map and a satellite constellation. Both occlusion and absorptioneffects of the environment are considered. A rugged mobile platform wasdesigned to collect data in order to generate the point cloud maps. It wasdeployed during the Canadian winter known for large amounts of snow andextremely low temperatures. The test environments include a highly dense borealforest and a university campus with high buildings. The experiment resultsindicate that the model performs well in both structured and unstructuredenvironments

Predicting GNSS satellite visibility from dense point clouds