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基于激光雷达探测的飞机尾流融合预测方法

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为提高基于激光雷达的飞机尾流探测反演精度,根据扫描出的径向风速数据,建立了基于Kolmogorov结构函数的大气背景湍流耗散率(EDR)估计方法;然后基于两阶段消散预测模型,计入湍流对尾流消散过程的影响,实现基于历史探测数据的尾涡强度环量和涡核运动趋势的预测;通过环境探测数据与预测模型的结合,提高尾涡特性参数的反演精度.研究表明,相较于反演算法,采用本文模型预测的尾涡轨迹在径向距离和角度的精度上分别提高了59.5%、64.8%.
Aircraft wake fusion prediction method based on LiDAR detection
To improve the accuracy of aircraft wake detection and inversion based on LiDAR,an estimation method for atmospheric background turbulence dissipation rate(EDR)on the basis of Kolmogorov structure function is estab-lished according to the scanned radial wind speed data.Then,on the strength of a probabilistic two-phase wake vortex Decay and Transport Model,the influence of turbulence on the wake dissipation process is taken into account to a-chieve the prediction of wake intensity circulation and vortex core motion trend based on historical detection data.By combining environmental detection data with predictive models,the inversion accuracy of wake characteristic parame-ters is improved.The research is shown that tail vortex trajectories predicted using the model in this paper are 59.5%and 64.8%more accurate in terms of radial distance and angle,respectively compared to the inverse algorithm.

wake detectionturbulence estimationLiDARwake vortex flow fieldfusion prediction

魏志强、吕振海

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中国民航大学空中交通管理学院,天津 300300

尾流探测 湍流估计 激光雷达 尾涡流场 融合预测

国家自然科学基金中央高校基本科研业务费专项波音基金

U2133210312202106620221010014

2024

激光与红外
华北光电技术研究所

激光与红外

CSTPCD北大核心
影响因子:0.723
ISSN:1001-5078
年,卷(期):2024.54(3)
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