scholarly journals Method of radial velocities for the estimation of aircraft wake vortex parameters from data measured by coherent Doppler lidar

2015 ◽  
Vol 23 (19) ◽  
pp. A1194 ◽  
Author(s):  
I.N. Smalikho ◽  
V.A. Banakh ◽  
F. Holzäpfel ◽  
S. Rahm
2008 ◽  
Vol 45 (4) ◽  
pp. 1148-1155 ◽  
Author(s):  
Stephan Rahm ◽  
Igor Smalikho

2016 ◽  
Vol 119 ◽  
pp. 14008 ◽  
Author(s):  
Songhua Wu ◽  
Bingyi Liu ◽  
Jintao Liu

Atmosphere ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 49
Author(s):  
Xiaoying Liu ◽  
Xinyu Zhang ◽  
Xiaochun Zhai ◽  
Hongwei Zhang ◽  
Bingyi Liu ◽  
...  

The observation and identification of wake vortex are considered important factors to reduce aviation accidents and increase airport capacity. In addition to aircraft parameters, the evolution process of the wake vortex is strongly related to atmospheric conditions, including crosswind, headwind, atmospheric turbulence, and temperature stratification. Crosswind generally affects the wake vortex trajectories by transporting them to the downwind direction. Additionally, the circulation attenuation of wake vortex is also influenced by crosswind shear or turbulence related to crosswind. This paper implemented the range height indicator (RHI) scanning mode of pulsed coherent Doppler lidar (PCDL) to study the influence of crosswind on wake vortex evolution. The crosswind was obtained from the non-wake vortex regions of the RHI sectors. The method, based on the measurements of radial velocity and spectrum with the broadening feature, was performed to locate wake vortex cores. The wake vortex trajectories with various crosswind strengths were comprehensively analyzed.


2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Weijun Pan ◽  
Zhengyuan Wu ◽  
Xiaolei Zhang

The aircraft wake vortex has important influence on the operation of the airspace utilization ratio. Particularly, the identification of aircraft wake vortex using the pulsed Doppler lidar characteristics provides a new knowledge of wake turbulence separation standards. This paper develops an efficient pattern recognition-based method for identifying the aircraft wake vortex measured with the pulsed Doppler lidar. The proposed method is outlined in two stages. (i) First, a classification model based on support vector machine (SVM) is introduced to extract the radial velocity features in the wind fields by combining the environmental parameters. (ii) Then, grid search and cross-validation based on soft margin SVM with kernel tricks are employed to identify the aircraft wake vortex, using the test dataset. The dataset includes wake vortices of various aircrafts collected at the Chengdu Shuangliu International Airport from Aug 16, 2018, to Oct 10, 2018. The experimental results on dataset show that the proposed method can identify the aircraft wake vortex with only a small loss, which ensures the satisfactory robustness in detection performance.


2017 ◽  
Vol 30 (6) ◽  
pp. 588-595 ◽  
Author(s):  
I. N. Smalikho ◽  
V. A. Banakh ◽  
A. V. Falits

2011 ◽  
Vol 40 (6) ◽  
pp. 811-817
Author(s):  
吴永华 WU Yong-hua ◽  
胡以华 HU Yi-hua ◽  
戴定川 DAI Ding-chuan ◽  
徐世龙 XU Shi-long ◽  
李今明 LI Jin-ming

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