## Abstract

Variation of the atmospheric refraction index due to turbulent fluctuations is one of the key factors that affect the performance of electro-optical and infrared systems and sensors. Therefore, any prior knowledge about the degree of variation in the refractive index is critical in the success of field studies such as search and rescue missions, military applications, and remote sensing studies where these systems are used frequently. There are many studies in the literature in which the optical turbulence effects are modeled by estimation of the refractive index structure parameter, ${\mathrm{C}}_{n}^{2}$, from meteorological data for all levels of the atmosphere. This paper presents a modified approach for bulk-method-based ${\mathrm{C}}_{n}^{2}$ estimation. According to this approach, conventional wind speed, humidity, and temperature values above the surface by at least two levels are used as input data for Monin–Obukhov similarity theory in the estimation of similarity scaling constants with a finite difference approximation and a bulk-method-based ${\mathrm{C}}_{n}^{2}$ estimation. Compared with the bulk method, this approach provides the potential for using more than two levels of standard meteorological data, application of the scintillation effects of estimated ${\mathrm{C}}_{n}^{2}$ on the images, and a much simpler solution than traditional ones due to elimination of the roughness parameters, which are difficult to obtain and which increase the complexity, the execution time, and the number of additional input parameters of the algorithm. As a result of these studies, Atmospheric Turbulence Model Software is developed and the results are validated in comparison to the ${\mathrm{C}}_{n}^{2}$ model presented by Tunick.

© 2013 Optical Society of America

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