Revisiting Multi-GNSS Navigation for UAVs - An Equivariant Filtering Approach

This study introduces equivariant filtering as a powerful tool for refining state estimation in unmanned aerial vehicles (UAVs). Equivariant filters offer faster convergence rates and greater robustness to initial state errors compared to traditional methods by exploiting mathematical symmetries. The research demonstrates their effectiveness in sensor fusion using GNSS and IMU data and validates their practicality in real-world scenarios with the INSANE Dataset. This innovation holds immense promise for enhancing UAV state estimation in real-world environments.