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Wavefront sensorless multi-conjugate adaptive optics for imaging in deep atmospheric turbulence: preliminary numerical analysis

机译:Wavefront无传感器多共轭自适应光学,用于深度大气湍流成像:初步数值分析

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This paper deals with the problem of imaging in deep atmospheric turbulence conditions such as the ones encountered in long near-horizontal propagation scenarios. Under such conditions, anisoplanatism as well as the presence of intensity scintillations prevent efficient use of conventional single-wavefront corrector adaptive optics systems. Multi-conjugate adaptive optics (MCAO) techniques have been successfully demonstrated in the field of astronomy to mitigate anisoplanatism effects and improve correction on extended objects in weak atmospheric turbulence conditions. However these techniques typically require the use of several wavefront sensors which increases system complexity, and are impacted by the presence of intensity scintillations. We propose to use a wavefront sensorless MCAO method based solely on the optimization of image quality metrics. In this method, the commands applied to the deformable mirrors are computed from a metric derived directly from the compensated image. The method has the advantage of being more robust to scintillations and does not require wavefront sensors. In this preliminary numerical study, we evaluate the benefit of the MCAO approach in deep turbulence.
机译:本文涉及在深度大气湍流条件下成像的问题,例如在长时间近的近水平传播场景中遇到的。在这种条件下,基位血统以及强度闪烁的存在防止了传统的单波线校正器自适应光学系统的有效使用。在天文领域中成功地证明了多共轭自适应光学(MCAO)技术,以减轻弱大气湍流条件下的延伸对象的缩放。然而,这些技术通常需要使用几个波前传感器,这些传感器增加了系统复杂性,并且受强度闪烁的存在影响。我们建议仅基于图像质量指标优化的波前无传感器MCAO方法。在该方法中,应用于可变形镜的命令从直接从补偿图像导出的度量计算。该方法具有更强大地闪烁的优点,并且不需要波前传感器。在这项初步数值研究中,我们评估了MCAO方法在深处湍流中的益处。

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