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Measurement and data-processing approach for estimating the spatial statistics of turbulence-induced index of refraction fluctuations in the upper atmosphere

机译：估算高层大气湍流引起的折射率波动的空间统计量的测量和数据处理方法

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摘要

We present a method of data reduction and analysis that has been developed for a novel experiment to measure the spatial statistics of atmospheric turbulence in the tropopause. We took measurements of temperature at 15 points on a hexagonal grid for altitudes from 12,000 to 18,000 m while suspended from a balloon performing a controlled descent. From the temperature data we estimate the index of refraction and study the spatial statistics of the turbulence-induced index of refraction fluctuations. We present and evaluate the performance of a processing approach to estimate the parameters of isotropic models for the spatial power spectrum of the turbulence. In addition to examining the parameters of the von Karman spectrum, we have allowed the so-called power law to be a parameter in the estimation algorithm. A maximum-likelihood-based approach is used to estimate the turbulence parameters from the measurements. Simulation results presented here show that, in the presence of the anticipated levels of measurement noise, this approach allows turbulence parameters to be estimated with good accuracy, with the exception of the inner scale.
机译：我们提出了一种数据缩减和分析方法，该方法已针对一项新颖的实验进行开发，以测量对流层顶中大气湍流的空间统计数据。我们在六边形网格上的15个点进行了温度测量，高度从12,000到18,000 m，同时悬挂在执行受控下降的气球上。从温度数据中，我们估算折射率，并研究湍流引起的折射率波动的空间统计。我们提出并评估一种处理方法的性能，以估计湍流空间功率谱的各向同性模型的参数。除了检查冯卡曼光谱的参数外，我们还允许所谓的幂定律成为估计算法中的参数。基于最大似然法的方法用于根据测量结果估计湍流参数。此处给出的仿真结果表明，在预期的测量噪声水平下，该方法允许以良好的精度估算湍流参数（内部刻度除外）。

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