When a beam propagates through atmospheric turbulence over a known distance, the target beam profile deviates from the projected profile of the beam on the receiver. Intuitively, the unwanted distortion provides information about the atmospheric turbulence. This information is crucial for guiding adaptive optic systems and improving beam propagation results. In this paper, we propose an entropy study based on the image from a plenoptic sensor to provide a measure of information content of atmospheric turbulence. In general, lower levels of atmospheric turbulence will have a smaller information size while higher levels of atmospheric turbulence will cause significant expansion of the information size, which may exceed the maximum capacity of a sensing system and jeopardize the reliability of an AO system. Therefore, the entropy function can be used to analyze the turbulence distortion and evaluate performance of AO systems. In fact, it serves as a metric that can tell the improvement of beam correction in each iteration step. In addition, it points out the limitation of an AO system at optimized correction as well as the minimum information needed for wavefront sensing to achieve certain levels of correction. In this paper, we will demonstrate the definition of the entropy function and how it is related to evaluating information (randomness) carried by atmospheric turbulence.
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