Wind Measurement and Simulation Techniques in Multi-Rotor Small Unmanned Aerial Vehicles
Pramod Abichandani, Deepan Lobo, Gabriel Ford, Donald J. Bucci, Moshe Kam
Abstract
Wind disturbance presents a formidable challenge to the flight performance of multi-rotor small unmanned aerial vehicles (sUAVs). This paper presents a comprehensive review of techniques for measuring wind speed and airspeed for multi-rotor sUAVs. Three categories of sensing techniques are reviewed: flow sensors, anemometers, and tilt-angle based approaches. We also review techniques for generating wind disturbances in simulation. Wind simulation techniques that use power spectral density (PSD) functions, computational fluid dynamics (CFD), and probabilistic models are examined. Finally, we provide an open-source Python implementation of the Dryden wind turbulence model and embedded code to interface with an ultrasonic anemometer.