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1.中国民航大学 民航空管研究院, 天津 300300
2.中国民航大学 天津市智能信号与图像处理重点实验室, 天津 300300
3.中国民航大学 飞行技术学院, 天津 300300
4.中国民航大学 空管运行规划与安全技术重点实验室, 天津 300300
[ "陈星(1984-), 男, 河北辛集人, 硕士, 研究实习员, 2008年于天津商业大学获得学士学位, 2014年于中国民航大学获得硕士学位, 主要从事信号与信息处理、激光雷达技术及空间风场探测风切变识别等研究工作。E-mail:xchencauc@163.com" ]
[ "李贞(1992-), 女, 湖北荆州人, 硕士研究生, 2011年于中国民航大学获得学士学位, 主要从事测风激光雷达风场探测、低空风切变预警等研究工作, E-mail:135182299@qq.com" ]
收稿日期:2017-07-13,
录用日期:2017-9-5,
纸质出版日期:2018-04-25
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陈星, 李贞, 庄子波, 等. 测风激光雷达修正F因子的小尺度风切变检测算法[J]. 光学 精密工程, 2018,26(4):927-935.
Xing CHEN, Zhen LI, Zi-bo ZHUANG, et al. A small scale wind shear detection algorithm of modified F-factor for wind-profiling lidar[J]. Optics and precision engineering, 2018, 26(4): 927-935.
陈星, 李贞, 庄子波, 等. 测风激光雷达修正F因子的小尺度风切变检测算法[J]. 光学 精密工程, 2018,26(4):927-935. DOI: 10.3788/OPE.20182604.0927.
Xing CHEN, Zhen LI, Zi-bo ZHUANG, et al. A small scale wind shear detection algorithm of modified F-factor for wind-profiling lidar[J]. Optics and precision engineering, 2018, 26(4): 927-935. DOI: 10.3788/OPE.20182604.0927.
针对由复杂地形或地理环境等因素诱发范围小但强度大的晴空风切变无法被已有风切变算法检测的问题,提出一种测风激光雷达修正F因子来检测这种小尺度风切变的算法。将传统F因子中雷达无法直接测量的垂直风速分量通过理论模型转换为径向风速梯度的函数,将解算F因子的关键点落在得到径向风速梯度的问题上。先从晴空风场数据中提取出激光雷达下滑道扫描的风速廓线,再用最小二乘法计算风速廓线的径向梯度,进一步求解得到修正后的F因子,并根据其经验阈值来判别风切变,最后使用香港国际机场提供的实测激光雷达风场数据进行了实验验证。实验结果表明,当风切变范围在400~800 m时,该算法能够检测出现有斜坡算法无法检测到的小尺度风切变,并将小尺度风切变检测范围扩大2 NM。该方法利用地面激光雷达数据来衡量机载指标变化,并在检测几百米的小尺度风切变方面效果明显,对于降低风切变漏报率和提高风切变预警率都具有重要意义。
Aiming at the problem that a small but strong clear sky wind shear induced by the complex terrain or geographical environment and other factors cannot be detected by the existing wind shear detection algorithm
a small scale wind shear detection algorithm of lidar's modified F factor was put forward. The vertical wind speed component that could not be directly measured by lidar in traditional F-factor was converted into radial wind speed gradient by theoretical model
thus the key point for solving the F-factor fell on the way to obtaining the radial wind speed gradient. Firstly
the wind speed profile of lidar glide-path scanning was extracted from the clear sky field data. Then
by using the least squares method
radial gradient of the wind speed profile was calculated
and the modified F-factor was solved thereby
and the wind shear was determined according to its empirical threshold. Finally
the actual lidar wind field data provided by the Hong Kong International Airport were used for experimental verification. The experimental results show that when the wind shear in the range of 400m to 800m
the algorithm can detect the small scale wind shear which fail to be detected by the existing ramps algorithm
and enlarge the detection range for 2NM. The method proposed uses the ground lidar data to measure the change of the airborne index and has obvious effect in detecting the small scale wind shear of several hundred meters
which makes sense for reducing the missing report rate of the wind shear and improving the wind shear rate.
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