Quickly Sample and Reconstruct for Low-level Wind Shear Data Measured by Coherent Lidar

Low-level wind shear is a type of catastrophic weather that can cause aircraft to flip over, stall or even crash. Therefore, it is very important to detect and recognize this phenomenon. In recent years, coherent Lidar has been proposed to detect low-level wind shear, but the common recognition methods need large computation to inverse the wind field to recognize the type. In this paper, compressive sensing (CS) is put forward to quickly sample and reconstruct wind field data, which can greatly reduce the time required for wind field recognition. The wind field data involved in this paper are obtained by simulation. The results of data reconstruction prove that the method mentioned in this paper can describe the whole information with less samples and shorten the follow-up processing time to a certain extent, and improve the real-time recognition of low-level wind shear.