Simulation of Wake Vortex Detection with Airborne Doppler Lidar

2000 ◽  
Vol 37 (6) ◽  
pp. 984-993 ◽  
Author(s):  
Denis Darracq ◽  
Alexandre Corjon ◽  
Frédéric Ducros ◽  
Mike Keane ◽  
Daniel Buckton ◽  
...  
Keyword(s):  
Wake Vortex ◽  
Doppler Lidar ◽  
Vortex Detection

Research on the Technique of Aircraft Wake Vortex Detection Based on 1.5 μm Doppler Lidar

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
Keyword(s):  
Wake Vortex ◽  
Doppler Lidar ◽  
Aircraft Wake ◽  
Vortex Detection

scholarly journals A Deep Learning Framework Based on Multisensor Fusion Information to Identify the Airplane Wake Vortex

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yi Ai ◽  
Yuanji Wang ◽  
Weijun Pan ◽  
Dingjie Wu
Keyword(s):  
Deep Learning ◽  
Wind Field ◽  
Aviation Industry ◽  
Wake Vortex ◽  
Doppler Lidar ◽  
Multisensor Fusion ◽  
Rapid Improvement ◽  
Learning Framework ◽  
Detection And Identification ◽  
Vortex Detection

Along with the rapid improvement of the aviation industry, flight density also increases with the increase of flight demand, which directly leads to the increasingly prominent influence of wake vortex on flight safety and aviation control. In this paper, we propose a new joint framework—a deep learning framework—based on multisensor fusion information to address the detection and identification of wake vortices in the near-Earth phase. By setting multiple Doppler lidar in near-Earth flight areas at different airports, a large number of accurate wind field data are captured for wake vortex detection. Meanwhile, the airport surveillance radar is used to locate the wake vortex. In the deep learning framework, an end-to-end CNN-LSTM model has been employed to identify the airplane wake vortex from the data detected by Doppler lidar and the airport surveillance radar. The variables including the wind field matrix, positioning matrix, and the variance sequence are used as inputs to the CNN channel and LSTM channel. The identification and location information of the wake vortex in the wind field image will be output by the framework. Experiments show that the joint framework based on a multisensor possesses stronger ability to capture local feature and sequence feature than the traditional CNN or LSTM model.

Wake Vortex Detection and Tracking for Aircraft Formation Flight

2021 ◽  
pp. 1-19
Author(s):  
Ignace Ransquin ◽  
Denis-Gabriel Caprace ◽  
Matthieu Duponcheel ◽  
Philippe Chatelain
Keyword(s):  
Formation Flight ◽  
Wake Vortex ◽  
Detection And Tracking ◽  
Vortex Detection

scholarly journals Identification of Aircraft Wake Vortex Based on SVM

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Weijun Pan ◽  
Zhengyuan Wu ◽  
Xiaolei Zhang
Keyword(s):  
Environmental Parameters ◽  
Classification Model ◽  
Support Vector ◽  
Wake Vortex ◽  
Doppler Lidar ◽  
Pulsed Doppler ◽  
Wind Fields ◽  
Wake Turbulence ◽  
Aircraft Wake ◽  
Separation Standards

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.

Sensitivity Analysis of Wake Vortex Parameters Measured by Doppler Lidar

2015 ◽  
Author(s):  
Takashi Misaka ◽  
Shigeru Obayashi ◽  
Anton Stephan ◽  
Frank N. Holzäpfel ◽  
Thomas Gerz
Keyword(s):  
Sensitivity Analysis ◽  
Wake Vortex ◽  
Doppler Lidar

scholarly journals Ultrasonic Method for Aircraft Wake Vortex Detection

2007 ◽  
Vol 44 (3) ◽  
pp. 726-732 ◽  
Author(s):  
Rebecca J. Rodenhiser ◽  
William W. Durgin ◽  
Hamid Johari
Keyword(s):  
Ultrasonic Method ◽  
Wake Vortex ◽  
Aircraft Wake ◽  
Vortex Detection

Measurements of aircraft wake vortex parameters by a Stream Line Doppler lidar

2017 ◽  
Vol 30 (6) ◽  
pp. 588-595 ◽  
Author(s):  
I. N. Smalikho ◽  
V. A. Banakh ◽  
A. V. Falits
Keyword(s):  
Stream Line ◽  
Wake Vortex ◽  
Doppler Lidar ◽  
Aircraft Wake

Pulsed 1.5-$\mu$m LIDAR for Axial Aircraft Wake Vortex Detection Based on High-Brightness Large-Core Fiber Amplifier

2009 ◽  
Vol 15 (2) ◽  
pp. 441-450 ◽  
Author(s):  
A. Dolfi-Bouteyre ◽  
G. Canat ◽  
M. Valla ◽  
B. Augere ◽  
C. Besson ◽  
...  
Keyword(s):  
Fiber Amplifier ◽  
Wake Vortex ◽  
Large Core ◽  
High Brightness ◽  
Aircraft Wake ◽  
Vortex Detection ◽  
Core Fiber
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