Wind Estimation for Multirotor UAV Control based on Surface Pressure Distribution

The multirotor unmanned aerial vehicles (UAVs) are currently commonly used for various outdoor operations; However, gusts of wind may affect their stable control, and even lead to safety accidents. The common approach is to install wind sensors to obtain wind information for gust-resistant control, but traditional sensors are large, heavy, and slow to respond, making them unsuitable for small UAVs. In this paper, a compact, lightweight, fast-responsive wind estimation module is designed. When wind passes over the module, the surface pressure distribution information will be captured by the pressure sensors, and an artificial neural network is proposed to estimate the wind speed and direction. The effectiveness of the module was verified by testing it on a small UAV in the 5m/s wind field, achieving 4.09° direction estimation error and 0.34m/s speed estimation error.