Abstract. Wind data collection in the atmospheric boundary layer benefits from short term wind speed measurements using unmanned aerial vehicles. Fixed and rotary wing devices with diverse anemometer technology have been used in the past to provide such data, but the accuracy still has the potential to be increased. We developed a light weight drone (weight including sensor 45 min) for carrying an industry standard precision sonic anemometer. Accuracy tests have been performed with the isolated anemometer at high tilt angles in a calibration wind tunnel, with the drone flying in a large wind tunnel, and with the full system flying at different heights next to a bistatic lidar reference. The propeller-induced flow deflects the air to some extent, but this effect is compensated effectively. Our data fusion shows no signs of crosstalk between ground speed and wind speed. When compared with the bistatic lidar in very turbulent conditions, with 10 seconds averaging interval and with the UAV constantly circling around the measurement volume of the lidar reference, wind speed measurements have an average absolute bias of 1.9 % (0.073 m s⁻¹), wind elevation average absolute bias is 0.5°, and wind azimuth average absolute bias is 1.5°, indicating excellent accuracy under challenging and dynamic conditions. The system was finally flown in the wake of a wind turbine, successfully measuring the spatial velocity deficit distribution during forward flight, yielding results that are in very close agreement to lidar measurements and the theoretical distribution. We believe that the results presented in this paper can provide important information for designing flying systems for precise air speed measurements either for short duration at multiple locations (battery powered) or for long duration at a single location (power supplied via cable). UAVs that are able to accurately measure three-dimensional wind might be used as cost effective and flexible addition to measurement masts and lidar scans.

中文翻译：

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借助超声波风速计实现准确，实用的基于无人机的风速测量

摘要。大气边界层的风数据收集得益于使用无人机进行的短期风速测量。过去已使用具有不同风速计技术的固定翼和旋翼设备来提供此类数据，但精度仍有可能提高。我们开发了一种轻型无人机（包括传感器在内的重量为45分钟），用于携带行业标准的精密声波风速计。已经使用隔离风速计在校准风洞中以高倾斜角度进行了精度测试，无人机在大型风洞中飞行，并且整个系统在不同的高度下飞行，并靠近双基地激光雷达参考。螺旋桨引起的气流使空气发生一定程度的偏转，但这种效果得到了有效补偿。我们的数据融合显示地面速度和风速之间没有串扰的迹象。与双动激光雷达相比，在非常动荡的条件下，平均间隔为10秒，并且无人机不断围绕激光雷达参考的测量体积盘旋时，风速测量的平均绝对偏差为1.9％（0.073 m s^-1），风标高平均绝对偏差为0.5°，风向方位角平均绝对偏差为1.5°，这表明在挑战性和动态条件下的出色准确性。该系统最终在风力涡轮机后飞行，成功地测量了前向飞行期间的空间速度赤字分布，得出的结果与激光雷达的测量值和理论分布非常接近。我们相信，本文介绍的结果可以为设计用于精确风速测量的飞行系统提供重要信息，无论是在多个位置的短时间内（电池供电）还是在单个位置的长时间（通过电缆供电）。