Volume 10 Issue 4
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SHEN Chun, LI Jianbing, GAO Hang, et al. Aircraft wake vortex behavior prediction based on data assimilation[J]. Journal of Radars, 2021, 10(4): 632–645. doi: 10.12000/JR21007
Citation: SHEN Chun, LI Jianbing, GAO Hang, et al. Aircraft wake vortex behavior prediction based on data assimilation[J]. Journal of Radars, 2021, 10(4): 632–645. doi: 10.12000/JR21007
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Aircraft Wake Vortex Behavior Prediction Based on Data Assimilation

doi: 10.12000/JR21007
  • 1.

    College of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, China

  • 2.

    Hong Kong Observatory, Hong Kong 999077, China

Funds:  The National Natural Science Foundation of China (61490649, 61771479, 61625108), Hunan Natural Science Foundation for Distinguished Young Scholars (2018JJ1030)
More Information
  • Corresponding author: LI Jianbing, jianbingli@nudt.edu.cn
  • Received Date: 2021-01-22
  • Rev Recd Date: 2021-03-16
    • Available Online: 2021-04-02
  • Publish Date: 2021-08-28
    Abstract
  • Aircraft wake are a couple of counter-rotating vortices generated by a flying aircraft, which can pose a serious hazard to follower aircraft. The behavior prediction of it is a key issue for air traffic safety management. To this end, we propose a prediction method based on data assimilation, which can be used to predict the evolution and hazard area of aircraft wake vortex from the vortex-core’s positions and circulation. To construct our wake vortex prediction model, we use linear shear and least square estimation. In addition, we use a data assimilation model based on the unscented Kalman filter to instantly correct the predicted trajectories. Our experimental results show that the proposed method performs well and runs steadily, thus, providing an effective tool for aircraft wake vortex prediction and support for the establishment of dynamic wake separation in air traffic management.

     

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