湍流廓线激光雷达的数据处理方法
Data processing techniques for turbulence profile Lidar
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摘要: 湍流廓线激光雷达是近十年出现的测量大气湍流强度廓线的新技术,目前数据处理已成为该技术的关键环节。对湍流廓线激光雷达的数据处理方法进行了详细地描述,重点研究了双光斑图像背景阈值计算方法与大气湍流强度廓线反演算法。比较了迭代法、最大类间方差法和统计法三种背景阈值计算方法分别在强信号与弱信号下的计算结果,得出统计法是比较适合双光斑图像的背景阈值计算方法。在背景阈值计算的基础上对图像进行分割并计算得到双光斑的质心距,统计多帧图像的质心距起伏得到达角起伏方差。然后利用HV-21模型模拟了从到达角起伏方差反演大气湍流强度廓线的算法,所得结果与原始值大小相近、整体变化趋势一致,但是不能反映原始值的细节变化趋势。Abstract: The atmospheric turbulence profile Lidar is a new technique presented near ten years which is used to measure the optical turbulence altitude profile. Nowadays data processing becomes a significant problem of this technique. The data processing methods of the turbulence profile lidar were described in detail. Methods to calculate threshold values of dual light spot images and inversion of atmospheric turbulence profile were studied mainly. These threshold values calculated by iterative method, maximum classes variance method and statistic method were compared with each other, statistic method was an appropriate method to calculate threshold values of dual light spot images. And then coordinates of dual light spot were obtained and centroid distances were calculating based this threshold values. Arrival angle fluctuations were computed with centroid distances of multiple images. Inversion of atmospheric turbulence profile from arrival angle fluctuations was simulated with HV-21 model. These values retrieved and original data were in same magnitudes and same integrative trend but differed in partial curvilinear trend.