Factor Graph Optimization-Based Magnetic Navigation Using a Quantum Magnetometer in GNSS-Denied Environments

Dongwoo Lee*, Deok-Young Lee, Hyochoong Bang

We propose a Factor Graph Optimization (FGO)-based magnetic anomaly navigation (MagNav) framework to reduce error accumulation in inertial navigation systems (INS) under GNSS-denied conditions. The proposed approach formulates MagNav as a graph-based optimization problem by integrating INS outputs with high-sensitivity measurements from a quantum magnetometer, enabling robust map matching through joint optimization of navigation states over time while accounting for sensor noise and map uncertainty. The proposed method is validated using magnetic maps constructed from real flight data, demonstrating the feasibility of FGO-based MagNav in practical scenarios. Experimental results show that the proposed approach achieves an RMSE of 7.6 m, corresponding to a 96.7% improvement compared to dead reckoning (228 m), while maintaining stable performance in low-gradient regions. The proposed framework provides a robust and high-precision navigation solution in GNSS-denied environments. Keywords: magnetic navigation, factor graph optimization, quantum magnetometer, GNSS-denied navigation

Speaker 이동우* 한국과학기술원