Sensing and Estimation of Airflow Angles and Atmospheric Winds for Small Unmanned Aerial Vehicles

Abstract

This dissertation focuses on development of new sensing, estimation, and analysis methods for unmanned aerial vehicle (UAV) operations in dynamic wind fields. Three main problems are studied, including airflow angle estimation, 3D wind estimation, and UAV wake encounter identification, simulation, and validation. A thorough survey is performed first on wind sensing and estimation methods using fixed-wing UAVs. Four flow angle estimation filters are then proposed and validated for accurate UAV flow angle estimation at low cost. Furthermore, two 3D wind estimation filters are proposed for small fixed-wing UAVs and validated by utilizing different wind models. Finally, a novel UAV wake encounter simulation platform is developed to simulate UAV response during wake encounters and compared with results from close formation wake encounter flight.