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arXiv 1807.04586astro-ph.IM
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部分校正模式下Shack-Hartmann波前传感器灵敏度损失因子的估计

Shack-Hartmann wavefront sensor sensitivity loss factor estimation in partial correction regime

Guido Agapito, Carmelo Arcidiacono, Simone Esposito

AI总结:

针对自适应光学中波前传感器闭环与衍射极限校准下灵敏度存在差异的问题,提出一种基于闭环传递函数参数、从闭环数据估计Shack-Hartmann波前传感器灵敏度损失因子的算法,且该算法可推广至其他波前传感器。

摘要:

在典型的自适应光学应用中,大气残余湍流会影响波前传感器的响应,降低其灵敏度。另一方面,波前传感器通常在衍射极限条件下校准,因此相互作用矩阵的灵敏度与闭环状态下的灵敏度存在差异。我们将这两种灵敏度的比值称为灵敏度损失因子,必须对其进行估计才能获取校准良好的测量结果。光斑尺寸测量可以给出不错的估计值,但它仅适用于光斑采样充分且在光瞳上分布均匀的系统。我们提出了一种基于闭环传递函数已知参数、从闭环数据估计灵敏度损失因子的算法。为简便起见,本文选用Shack-Hartmann WFS(波前传感器)进行研究,但我们提出的算法可推广至其他类型的WFS。

英文摘要:

In typical adaptive optics applications, the atmospheric residual turbulence affects the wavefront sensor response decreasing its sensitivity. On the other hand, wavefront sensors are generally calibrated in diffraction limited condition, and, so, the interaction matrix sensitivity differs from the closed loop one. The ratio between the two sensitivities, that we will call the sensitivity loss factor, has to be estimated to retrieve a well-calibrated measurement. The spots size measurement could give a good estimation, but it is limited to systems with spots well sampled and uniform across the pupil. We present an algorithm to estimate sensitivity loss factor from closed loop data, based on the known parameters of the closed loop transfer functions. Here we preferred for simplicity the Shack-Hartmann WFS, but the algorithm we propose can be extended to other WFSs.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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