Qiao Wenyou, Gao Zhishan, Yuan Qun, Chen Lu, Guo Zhenyan, Huo Xiao, Wang Qian
School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China.
Jiangsu Energy Measurement Data Center, Jiangsu Institute of Metrology, Nanjing 210023, China.
Sensors (Basel). 2025 Jun 30;25(13):4085. doi: 10.3390/s25134085.
High aspect ratio (HAR) sample-induced aberrations seriously affect the topography measurement for the bottom of the microstructure by coherence scanning interferometry (CSI). Previous research proposed an aberration compensating method using deformable mirrors at the conjugate position of the pupil. However, it failed to compensate for the shift-variant aberrations introduced by the HAR hybrid trench array composed of multiple trenches with different parameters. Here, we propose a computational aberration correction method for measuring the topography of the HAR structure by the particle swarm optimization (PSO) algorithm without constructing a database and prior knowledge, and a phase filter in the spatial frequency domain is constructed to restore interference signals distorted by shift-variant aberrations. Since the aberrations of each sampling point are basically unchanged in the field of view corresponding to a single trench, each trench under test can be considered as a separate isoplanatic region. Therefore, a multi-channel aberration correction scheme utilizing the virtual phase filter based on isoplanatic region segmentation is established for hybrid trench array samples. The PSO algorithm is adopted to derive the optimal Zernike polynomial coefficients representing the filter, in which the interference fringe contrast is taken as the optimization criterion. Additionally, aberrations introduce phase distortion within the 3D transfer function (3D-TF), and the 3D-TF bandwidth remains unchanged. Accordingly, we set the non-zero part of the 3D-TF as a window function to preprocess the interferogram by filtering out the signals outside the window. Finally, experiments are performed in a single trench sample and two hybrid trench array samples with depths ranging from 100 to 300 μm and widths from 10 to 30 μm to verify the effectiveness and accuracy of the proposed method.
高深宽比(HAR)样品引起的像差严重影响了基于相干扫描干涉术(CSI)的微结构底部形貌测量。先前的研究提出了一种在光瞳共轭位置使用可变形镜的像差补偿方法。然而,它未能补偿由具有不同参数的多个沟槽组成的HAR混合沟槽阵列引入的位移变化像差。在此,我们提出一种计算像差校正方法,通过粒子群优化(PSO)算法测量HAR结构的形貌,无需构建数据库和先验知识,并在空间频域中构建相位滤波器来恢复因位移变化像差而失真的干涉信号。由于在对应于单个沟槽的视场中每个采样点的像差基本不变,因此每个被测沟槽可被视为一个单独的等晕区。因此,针对混合沟槽阵列样品建立了一种基于等晕区分割的利用虚拟相位滤波器的多通道像差校正方案。采用PSO算法推导表示滤波器的最优泽尼克多项式系数,其中干涉条纹对比度作为优化准则。此外,像差在三维传递函数(3D-TF)内引入相位失真,且3D-TF带宽保持不变。相应地,我们将3D-TF的非零部分设置为窗函数,通过滤除窗外信号对干涉图进行预处理。最后,在深度范围为100至300μm、宽度为10至30μm的单个沟槽样品和两个混合沟槽阵列样品上进行实验,以验证所提方法的有效性和准确性。