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Error analysis for the Fourier domain offset estimation algorithm

机译:傅里叶域偏移估计算法的误差分析

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摘要

The offset estimation algorithm is crucial for the accuracy of the Shack-Hartmann wave-front sensor. Recently, the Fourier Domain Offset (FDO) algorithm has been proposed for offset estimation. Similar to other algorithms, the accuracy of FDO is affected by noise such as background noise, photon noise, and 'fake' spots. However, no adequate quantitative error analysis has been performed for FDO in previous studies, which is of great importance for practical applications of the FDO. In this study, we quantitatively analysed how the estimation error of FDO is affected by noise based on theoretical deduction, numerical simulation, and experiments. The results demonstrate that the standard deviation of the wobbling error is: (1) inversely proportional to the raw signal to noise ratio, and proportional to the square of the sub aperture size in the presence of background noise; and (2) proportional to the square root of the intensity in the presence of photonic noise. Furthermore, the upper bound of the estimation error is proportional to the intensity of 'fake' spots and the sub-aperture size. The results of the simulation and experiments agreed with the theoretical analysis. (C) 2015 Elsevier B.V. All rights reserved.
机译:偏移估计算法对于Shack-Hartmann波前传感器的准确性至关重要。最近,已经提出了傅里叶域偏移(FDO)算法来进行偏移估计。与其他算法相似,FDO的精度受诸如背景噪声,光子噪声和“假”斑点之类的噪声影响。但是,在以前的研究中,没有对FDO进行足够的定量误差分析,这对于FDO的实际应用非常重要。在这项研究中,我们基于理论推论,数值模拟和实验,定量分析了FDO的估计误差如何受到噪声的影响。结果表明,摆动误差的标准偏差为:(1)与原始信噪比成反比,与存在背景噪声的情况下与子孔径大小的平方成正比; (2)与存在光子噪声时强度的平方根成正比。此外,估计误差的上限与“假”光斑的强度和子孔径大小成正比。仿真和实验结果与理论分析相吻合。 (C)2015 Elsevier B.V.保留所有权利。

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