Algorithms of 3D Wind Field Reconstructing by Lidar Remote Sensing Data

In this paper, we analyzed the performance of wind vector field recovery from the wind lidar measurements. Wind lidar (LIDAR – Light Identification Detection And Ranging) remotely measures the wind radial speed by using the Doppler principle. Algorithms of the wind vector reconstruction using different versions of the least squares method are considered. In particular, the versions of weighted least squares (WLS) are considered, as well as the use of data spikes filtering procedures in the source data. The weights were calculated inversely with the local approximation error. As the initial data, the data of real measurements obtained in various wind conditions were used. The situations of a stationary wind field, a wind field with speed gusts, a wind field with fluctuations in direction, a wind field of variable speed and direction are considered. Lidar data were obtained for a region with a low-hilly terrain; therefore, even in the case of a stationary in time, the wind field was characterized by spatial heterogeneity. The questions of the use of regularization methods are considered. The analysis of the influence of the size of the averaging region on the quality of the recovery process was carried out.