Application of low-altitude wind shear recognition algorithm and laser wind radar in aviation meteorological services

Abstract

The rapid development of the aviation industry has attracted great attention to aviation safety, and the identification and early warning of low-level wind shear have become crucial. Therefore, it is also necessary to improve the performance of laser wind radar technology and achieve accurate recognition of low-level wind shear. In this regard, this study is based on laser wind radar technology and uses the K-neighborhood frequency method to denoise radar data. And based on the least squares fitting method, two-dimensional synthetic wind shear is obtained, and a low altitude wind shear recognition model based on laser wind radar is constructed. These test results confirm that the correlation coefficient values of the wind speed fitting curve measured by the laser detection radar on sunny, cloudy, and fog days are 0.978, 0.954, and 0.961, respectively. And the correlation coefficient values of wind direction fitting curve are 0.984, 0.982, and 0.952, respectively. On sunny, cloudy, and fog days, the recognition accuracy values of the low-level wind shear recognition model are 85.92, 82.17, and 72.43%, respectively. And the recognition accuracy values of wind analyzer radar are 70.18, 62.57, and 55.89%, respectively. In practical applications, the low-level wind shear recognition model accurately recognizes the occurrence of low-level wind shear. This study has achieved accurate recognition of low-level wind shear and has better performance compared to other existing radars. It has played an important reference role in aviation safety.

Keywords

• wind shear
• laser wind radar
• aviation
• k-neighborhood frequency
• least squares fitting