Abstract
A large number of model probability density functions (PDFs) are used to analyze atmospheric scintillation statistics. We have analyzed scintillation data from two different experimental setups covering a range of scintillation strengths to determine which candidate model PDFs best describe the experimental data. The PDFs were fitted to the experimental data using the method of least squares. The root-mean-squared fitting error was used to monitor the goodness of fit. The results of the fitting were found to depend strongly on the scintillation strength. We find that the log normally modulated Rician and the log normal PDFs are the best fit to the experimental data over the range of scintillation strengths encountered.
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