LAUSR

The analysis of aircraft wake vortex is of great significance for the improvement of airspace utilization. To overcome the shortcomings of traditional manual methods which are unable to produce satisfactory results on the great number of wake vortex data with high accuracy recognition, a fast automatic method is proposed based on Random Forests (RF). The development of our model is outlined as follows: (1) A wake vortex dataset that consisted of various aircraft measured by Wind3D 6000 LiDAR was collected at Chengdu Shuangliu International Airport from Aug. 16, 2018 to Oct. 10, 2018. (2) The optimal parameters were determined by grid search by visualizing the characteristic values of wake vortices, to get the optimal RF model, allowing high efficiency as well as improved accuracy. In terms of evaluation metrics, the experimental results showed that the method can effectively recognize the wake data in different situations, exhibiting good robustness.