量子电子学报, 2014, 31 (3): 348, 网络出版: 2014-06-03
DCIM激光雷达测量湍流廓线反演算法及数值仿真研究
Inversion algorithm and numerical simulation of DCIM lidar measurement turbulence profile
大气光学 湍流廓线 反演算法 激光雷达 数值仿真 atmospheric optics inversion algorithm turbulence profile lidar numerical simulation
摘要
提出了一种基于广义Hufnagel-Valley模型的差分光柱像运动(DCIM)激光雷达测量湍流廓线的反演算法, 推导了数据平滑处理函数,通过对HV 5/7模型廓线数值仿真得出:真值反演时,反演廓线与理论模型廓线 最大相差约0.004个量级,反演廓线计算的r0、整层θ与理论值的相对误差绝对值均在0.5%以下;有10%随机 误差时, 20 km以下反演廓线与理论模型廓线最大相差约0.5个量级, 20 km以上误差增大,反演廓线计算的r0和 整层θ与理论值的相对误差绝对值约在10%和5%以下,满足实际激光大气传输应用;数据平滑处理函数不会影 响反演廓线随高度的变化特性。最后仿真验证了反演算法的普适性,可用于DCIM激光雷达测量不同地区的湍流廓线。
Abstract
The inversion algorithm of differential image collumn motion(DCIM) lidar measuring turbulence profile was proposed based on generalized Hufnagel-Valley model. The smoothing function of data was derived. Through numerical simulation of HV 5/7 model, some results were obtained. Without random error, the maximum difference between the inversion profile and HV 5/7 model profile is about 0.00order of magnitude. The absolute relative errors of r0 and the whole layer θ calculated by the inversion profiles are both less than 0.5%. With 10% random errors, the maximum difference between the inversion profiles and HV 5/7 model profile is about 0.5 order of magnitude below 20 km while it is bigger than 20 km. The absolute relative errors of r0 and the whole layer θ computed by the inversion profile are less than 10% and 5%. So it meets the actual application of laser propagation in the atmosphere. The smoothing function is suitable for practical application because it does not affect the distribution of the inversion profile with height. Finally, the universality of the algorithm was verified and the algorithm can be used to DCIM lidar to get profile.
黄克涛, 吴毅, 侯再红, 靖旭, 程知, 崔利果. DCIM激光雷达测量湍流廓线反演算法及数值仿真研究[J]. 量子电子学报, 2014, 31(3): 348. HUANG Ke-tao, WU Yi, HOU Zai-hong, JING Xu, CHENG Zhi, CUI Li-guo. Inversion algorithm and numerical simulation of DCIM lidar measurement turbulence profile[J]. Chinese Journal of Quantum Electronics, 2014, 31(3): 348.