Kim Jin-Hyok, Kim Chol-Hyon, Yun Tu-Hon, Hong Hui-Sung, Ho Kwang-Myong, Kim Kwang-Ho
Appl Opt. 2021 Mar 10;60(8):2282-2287. doi: 10.1364/AO.415903.
It is not easy to estimate self-mixing interferometry parameters, namely, the optical feedback factor and the linewidth enhancement factor from the self-mixing signals (SMSs) affected by noise such as speckle. These SMSs call for normalization, which is not only difficult, but also apt to distort the intrinsic information of the signals, thereby resulting in incorrect estimation of the parameters and the displacement reconstruction. In this paper, we present what we believe is a novel normalization method we call "local normalization," which enables more exact and simpler estimation and displacement retrieval compared to previous methods, for it is based on an analytic relation instead of approximation. The method is very noise-proof, and especially speckle-noise-proof as well. The method proposed can be applied to moderate and strong feedback regimes. The simplicity and accuracy of the method will provide a fine tool for a low-cost self-mixing displacement sensor with a high resolution of about 40 nm.
从受散斑等噪声影响的自混合信号（SMS）中估计自混合干涉测量参数，即光反馈因子和线宽增强因子并非易事。这些SMS需要进行归一化处理，这不仅困难，而且容易扭曲信号的固有信息，从而导致参数估计和位移重建错误。在本文中，我们提出了一种我们认为新颖的归一化方法，称为“局部归一化”，与以前的方法相比，它能够实现更精确、更简单的估计和位移检索，因为它基于解析关系而非近似关系。该方法具有很强的抗噪声能力，尤其是抗散斑噪声能力。所提出的方法可应用于中等和强反馈区域。该方法的简单性和准确性将为低成本、高分辨率约为40 nm的自混合位移传感器提供一个很好的工具。
