Maneuver Optimization for Simultaneous Airspeed Calibration and Wind Estimation

Abstract

[EN] The purpose of this work is to optimize systematically the maneuver required to identify the wind and calibrate the airspeed sensor of a subsonic aircraft using a GPS method. The optimization is based on sensitivity analyses that require a considerable number of flight simulations. To face this challenging computational effort, we adapted and parallelized a particle swarm optimization algorithm. We also introduced a new formulation of the sensor model in the Bernstein form. The results show stability using the selected formulation and bring out non-obvious aliasing and precision loss effects that depend on the maneuver configuration. The knowledge of these effects allowed us to fine-tune the maneuver in order to improve the estimation's precision. Finally, we validated the method using the JSBSim flight simulator under calm and light turbulence conditions.