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

机译:固定翼小无人空中系统的风力特征与映射

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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).
机译:本文介绍了使用无人驾驶飞机系统(UAS)的风力特征和映射的新方法。风图的产生对于高效轨迹的节能轨迹规划和动态飙升应用来检测剪切层。首先,分析了通过使用UA来估计定义未知风场(风速和方向)的参数的两种方法。通过将估计的风数据拟合到威布尔概率密度函数中来选择最佳方法。所获得的威布尔参数用于将数据推断成有限电网。然后提出了一种基于所谓的Xuibull外推方法(WM)的外推方法。实施的外推方法具有两个优点:它适用于不同高度的测量,并考虑测量的显着噪声分量。这种突破允许对风图的实时构造的可能性,这对于精确的轨迹规划和风力特征检测是必要的,例如阵风,剪切风或湍流。已使用真实的遥测数据来实现该方法。一旦获得外推数据,就执行分析以通过确定所选择的数据继续拟合到威布尔分布并遵循经验幂律(EPL)来验证数据。

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