Yoshino Hirokazu, Walls John Michael, Smith Roger
Appl Opt. 2017 Jun 1;56(16):4757-4765. doi: 10.1364/AO.56.004757.
The capability of coherence scanning interferometry has been extended recently to include the determination of the interfacial surface roughness between a thin film and a substrate when the surface perturbations are less than ∼10 nm in magnitude. The technique relies on introducing a first-order approximation to the helical complex field (HCF) function. This approximation of the HCF function enables a least-squares optimization to be carried out in every pixel of the scanned area to determine the heights of the substrate and/or the film layers in a multilayer stack. The method is fast but its implementation assumes that the noise variance in the frequency domain is statistically the same over the scanned area of the sample. This results in reconstructed surfaces that contain statistical fluctuations. In this paper we present an alternative least-squares optimization method, which takes into account the distribution of the noise variance-covariance in the frequency domain. The method is tested using results from a simulator and these show a significant improvement in the quality of the reconstructed surfaces.
最近，相干扫描干涉测量技术的能力得到了扩展，当表面扰动幅度小于约10纳米时，该技术可用于确定薄膜与基底之间的界面表面粗糙度。该技术依赖于对螺旋复场（HCF）函数引入一阶近似。HCF函数的这种近似使得能够在扫描区域的每个像素中进行最小二乘优化，以确定多层堆叠中基底和/或薄膜层的高度。该方法速度很快，但其实现假设频域中的噪声方差在样品的扫描区域上在统计上是相同的。这导致重建表面包含统计波动。在本文中，我们提出了一种替代的最小二乘优化方法，该方法考虑了频域中噪声方差 - 协方差的分布。使用模拟器的结果对该方法进行了测试，结果表明重建表面的质量有了显著提高。
