中文摘要：

针对不同的风切变在激光雷达图像上所呈现的不同纹理特性，提出了一种组合局部纹理特征和全局纹理特征的识别方法。先分别从激光雷达风切变图像中提取LBP特征和灰度-梯度共生矩阵特征，LBP特征反应图像的局部纹理，代表风场局部风速的变化，灰度-梯度共生矩阵特征反应图像的全局纹理，代表风场全局的风速变化，再通过典型相关分析对两种特征进行融合，最后采用最近邻分类器对三种风切变进行匹配识别。实验结果表明，该算法对三种低空风切变的平均识别率达到99．02％，与三种单一的纹理特征分类识别相比，分别提高了18．86％，5．88％和7．01％。

英文摘要：

As different wind shear presents different characteristics of texture on the laser radar images, a recognition algorithm which combines local and global texture features is proposed. Firstly, local Binary Pattern （ LBP ） features and Gray-Gradient Co-occurrence Matrix （GGCM） features are extracted from the laser radar images respectively, LBP features react the local texture of the images and represent the changes of wind speed of local wind farm, GGCM features react the global texture of the images and represent the speed changes of whole wind field. The two features are fused through Canonical Correlation Analysis（CCA） ,finally the nearest neighbor classifier is adopted to match three different wind shears. Experiment results show that the recognition rate of the proposed algorithm on the three kinds of low altitude wind shear can reach 99.02%. Compared with three kinds of single texture, the recognition rate is raised by 18.86% ,5.88% and 7.01% respectively.