3D Mapping Database Aided GNSS Based Collaborative Positioning Using Factor Graph Optimization

The recent development in vehicle-to-everything (V2X) communication opens a new opportunity to improve the positioning performance of road users. We explore benefit connecting raw data global navigation satellite system (GNSS) from agents. In urban areas, GNSS is highly degraded due signal blockage and reflection. 3D building model can play major role mitigating multipath non-line-of-sight (NLOS) effects. To combine benefits models V2X, we propose novel mapping aided (3DMA) GNSS-based collaborative method that makes use available surrounding receivers’ measurements. By complementarily integrating ray-tracing based 3DMA double difference technique, random errors (such as NLOS) are mitigated while eliminating systematic atmospheric delay clock/orbit biases) between user. accuracy robustness algorithm, factor graph optimization (FGO) employed optimize solutions among Multiple low-cost receivers used collect both static dynamic Hong Kong evaluate proposed algorithm by post-processing. reduce error over 30 meters less than 10 for users deep canyon.