To identify aircraft wake vortex by pulsed doppler LiDAR’s characteristics, a classification model based on k-nearest neighbor (KNN) was established in this paper. This approach by combining Hallock-Burnham model with pulsed doppler LiDAR’s characteristics to extract the feature parameters of radial velocity of wind field was pursued. Based on the test dataset, the KNN was employed to identify aircraft wake vortex in the context of nonuniform wind field. The performance of the proposed method was evaluated in terms of the accuracy (ACC) and the area under ROC curve (AUC). The ACC and the AUC of our technique on test dataset are 0.772 and 0.855, respectively. Experimental results are presented to illustrate the validity and robustness of the proposed approach to aircraft wake vortex.