GraphGNSSLib

active

GraphGNSSLib is an open-source C/C++ platform for GNSS positioning, RTK, and GNSS/INS research using factor graph optimization. It connects raw GNSS data — pseudorange, Doppler, carrier phase, ambiguity resolution — to nonlinear optimization and to ROS-based robotic systems.

Why it matters. GraphGNSSLib gives navigation and robotics researchers a practical bridge from GNSS measurements to modern optimization-based estimation, replacing classical EKF pipelines with a unified framework that can fuse heterogeneous measurements, handle outliers more flexibly, and reason over time.

Outputs: GitHub repository, code examples, ROS demos, integration with UrbanNav, and the foundational Factor Graph Optimization for GNSS/INS Integration: A Comparison with the Extended Kalman Filter (Wen, Pfeifer, Bai, Hsu) paper that was named 2024 Most-Cited Paper in NAVIGATION.

Started: 2020

Lab members involved

Weisong Wen

Research Pillars

Urban GNSS Reliability and Signal Error Modeling Environment-Aware and 3D Map-Aided PNT Optimization-Based Estimation and Factor Graphs Integrity, Fault Detection, and Safety-Quantifiable Localization Seamless Multi-Sensor PNT for Embodied Systems

Code Repository