Wind characterization and mapping using fixed-wing small unmanned aerial systems

Abstract

This paper presents a novel method for wind characterization and mapping by using an Unmanned Aircraft System (UAS). The generation of a wind map is vital in energy-efficient trajectory planning of efficient trajectories and dynamic soaring applications to detect the shear layer. Firstly, two methods to estimate the parameters that define an unknown wind field (wind speed and direction) by using a UAS are analyzed. The best method is selected by fitting the estimated wind data into a Weibull probability density function. The obtained Weibull parameters are used to extrapolate the data into a finite grid. Then an extrapolation method based on the so-called Weibull extrapolation Method (WM) is proposed. The implemented extrapolation method presents two advantages: it works with measurements at different heights and considers a significant noise component of the measurements. This break-through allows the possibility of real-time construction of a wind map, which is imperative for accurate trajectory planning and wind feature detection, such as gusts, shear wind or turbulence. Real telemetry data have been used in order to implement the method. Once the extrapolated data are obtained, an analysis is performed to validate the data by determining if the selected data continues fitting into a Weibull distribution and follows the Empirical Power Law (EPL).