Collaborative Vision-Integrated Pseudorange Error Removal: Team-Estimated Differential GNSS Corrections with no Stationary Reference Receiver

This paper presents an approach for generating Global Navigation Satellite System (GNSS) differential corrections by distributing GNSS and georeferenced vision measurements through a vehicle-to-vehicle (V2V) communications network. Conventionally, high-quality differential GNSS corrections are generated from a stationary reference receiver in close proximity to a set of mobile users. The proposed method, which is called Collaborative Vision Integrated Pseudorange Error Removal (C-VIPER), instead generates differential corrections using data from moving vehicles, thus eliminating the need for an infrastructure of stationary receivers. An important feature of the proposed algorithm is that individual differential corrections are computed for each satellite, so that corrections can be shared among users with different satellites in view. As demonstrated in simulation, measurement sharing significantly improves positioning accuracy in both the cross-track direction, where the quality of visual lane-boundary measurements is high, and the along-track direction, where the quality is low. Furthermore, because measurements are shared among many vehicles, the networked solution is robust to vision-sensor dropouts that may occur for individual vehicles.