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

Wonkeun Youn, Hyoung-Sik Choi, Am Cho, Sungyug Kim, Matthew B. Rhudy

2020IEEE Transactions on Aerospace and Electronic Systems28 citationsDOIOpen Access PDF

Abstract

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.

Topics & Concepts

AirspeedAerodynamicsRedundancy (engineering)GyroscopeAttitude controlControl theory (sociology)Wind speedAccelerometerComputer scienceAtmospheric modelEngineeringAngular velocityAerospace engineeringSimulationArtificial intelligenceControl (management)MeteorologyPhysicsOperating systemQuantum mechanicsInertial Sensor and NavigationAerospace and Aviation TechnologyTarget Tracking and Data Fusion in Sensor Networks
Aerodynamic Model-Aided Estimation of Attitude, 3-D Wind, Airspeed, AOA, and SSA for High-Altitude Long-Endurance UAV | Litcius