High-altitude vertical wind profile estimation using multirotor vehicles

Abstract

Capturing vertical profiles of the atmosphere and measuring wind conditions can be of significant value for weather forecasting and pollution monitoring however, collecting such data can be limited by current approaches using balloon-based radiosondes and expensive ground-based sensors. Multirotor vehicles can be significantly affected by the local wind conditions, and due to their under-actuated nature, the response to the flow is visible in the changes in the orientation. From these changes in orientation, wind speed and direction estimates can be determined, allowing accurate estimation with no additional sensors. In this work, we expand on and improve this method of wind speed and direction estimation and incorporate corrections for climbing flight to improve estimation during vertical profiling. These corrections were validated against sonic anemometer data before being used to gather vertical profiles of the wind conditions around Volcan De Fuego in Guatemala up to altitudes of 3000 m Above Ground Level (AGL). From the results of this work, we show we can improve the accuracy of multirotor wind estimation in vertical profiling through our improved model and some of the practical limitations of radiosondes that can be overcome through the use of UAS in this application.

Experimental Characterization of Propeller-Induced Flow (PIF) below a Multi-Rotor UAV

“…Multi-rotor drones consequently bear a large potential as suitable sensor-carrier for sonic anemometers, and corresponding approaches are reported in the literature [34][35][36][37][38][39]. So far, those approaches focus primarily on the measurement of the mean horizontal wind speed, often carrying miniaturized sonic anemometers with measurement geometries not fully capable of providing reliable measurements of the vertical wind component.…”

High-Resolution Profiling of Atmospheric Turbulence Using UAV Autopilot Data

“…Large and expensive UAVs capable of flying at high altitudes should bridge the gap between satellite data [15] and measurements obtained from ground-based networks in global NWP. At the same time, small and inexpensive UAVs can fill the gaps in obtaining data on profiles of the turbulent atmospheric boundary layer, especially in hard-to-reach or dangerous places [16][17][18][19] for short-term forecasting in local territories.…”

“…The main disadvantage of small and inexpensive UAVs is the limited battery life. In addition, the use of extra sensors, such as a pitot tube or an acoustic anemometer [19][20][21][22], can significantly increase the weight and cost of a drone. A possible solution to this problem is the use of the UAV itself as a detector of the state of the atmosphere.…”

“…A possible solution to this problem is the use of the UAV itself as a detector of the state of the atmosphere. The use of a UAV as a detector makes it possible to obtain information about the wind velocity in a turbulent atmosphere from autopilot data of hovering UAVs [17,19,[23][24][25][26][27][28][29].…”