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Improvement in error propagation in the Shack-Hartmann-type zonal wavefront sensors

机译:Shack-Hartmann型Zonal Wavefront传感器中的误差传播的改进

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Estimation of the wavefront from measured slope values is an essential step in a Shack-Hartmann-type wavefront sensor. Using an appropriate estimation algorithm, these measured slopes are converted into wavefront phase values. Hence, accuracy in wavefront estimation lies in proper interpretation of these measured slope values using the chosen estimation algorithm. There are two important sources of errors associated with the wavefront estimation process, namely, the slope measurement error and the algorithm discretization error. The former type is due to the noise in the slope measurements or to the detector centroiding error, and the latter is a consequence of solving equations of a basic estimation algorithm adopted onto a discrete geometry. These errors deserve particular attention, because they decide the preference of a specific estimation algorithm for wavefront estimation. In this paper, we investigate these two important sources of errors associated with the wavefront estimation algorithms of Shack-Hartmann-type wavefront sensors. We consider the widely used Southwell algorithm and the recently proposed Pathak-Boruah algorithm [J. Opt. 16, 055403 (2014)] and perform a comparative study between the two. We find that the latter algorithm is inherently superior to the Southwell algorithm in terms of the error propagation performance. We also conduct experiments that further establish the correctness of the comparative study between the said two estimation algorithms. (C) 2017 Optical Society of America
机译:在Shack-Hartmann型波前传感器中,根据测得的斜率值估计波前是一个必不可少的步骤。使用适当的估计算法,将这些测量的斜率转换为波前相位值。因此,波前估计的准确性在于使用所选的估计算法对这些测量的斜率值进行正确解释。波前估计过程中有两个重要的误差来源,即斜率测量误差和算法离散化误差。前者是由于斜率测量中的噪声或探测器的质心误差,后者是求解离散几何体上采用的基本估计算法方程的结果。这些误差值得特别注意,因为它们决定了波前估计的特定估计算法的偏好。在本文中,我们研究了与Shack-Hartmann型波前传感器的波前估计算法相关的这两个重要误差源。我们考虑了广泛使用的索思韦尔算法和最近提出的Pathak Boruah算法[J.opt 16, 055403(2014)],并对两者进行了比较研究。我们发现后一种算法在误差传播性能方面优于Southwell算法。我们还进行了实验,进一步验证了上述两种估计算法之间比较研究的正确性。(C) 2017美国光学学会

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