Aerodynamic Model-Aided Estimation of Attitude, 3-D Wind, Airspeed, AOA, and SSA for High-Altitude Long-Endurance UAV

摘要

This article proposes a novel dynamic model-aided navigation filter to estimate the safety-critical states of an aircraft including the effect of wind. Aerodynamic coefficients and control signals are used to predict the angular rates. Experimental flight results of a high-altitude long-endurance unmanned aerial vehicle (UAV) demonstrated improvement in attitude estimation compared to a model-based navigation algorithm that does not consider wind, as well as accurate attitude estimation without using gyroscope signals, demonstrating its effectiveness for analytical redundancy.