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 Kármán 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.
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