Calibration of Fixed-Wing UAV Aerodynamic Coefficients with Photogrammetry for VDM-based Navigation

Autonomous navigation is a crucial aspect for fixed-wing unmanned aerial vehicle operation when encountering disturbance or denial of GNSS signal reception. Vehicle dynamic model-based navigation improves the performance of methods based exclusively on introspective sensors (e.g., inertial, pressure) by incorporating mathematical models of aerodynamic forces and moments into the final navigation solution. Such an approach, however, requires model-coefficients that are calibrated to the specific vehicle being operated. We propose augmenting the self-calibration of these coefficients with additional observations derived from an on-board camera via photogrammetry. We confirm experimentally that irregular yet precise observations of vehicle absolute attitude obtained through such techniques greatly improve the determination of some aerodynamic coefficients that in turn reduce the error in autonomous positioning under GNSS signal outage.