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提出了一种基于空间像自适应降噪的投影物镜波像差检测方法。通过对空间像进行统计分析,获取空间像的噪声模型和噪声标准差模型。以噪声标准差为权重因子,利用加权最小二乘法对空间像进行主成分分解,可以实现对空间像的自适应、无损降噪,从而得到更为精确的主成分系数和泽尼克系数。使用光刻仿真软件PROLITH的仿真结果表明,在相同的噪声水平下,0.1λ像差幅值内,与基于空间像主成分分析的波像差检测技术相比,精度提高30%以上。在使用光刻实验平台测量Z8调整量的实验中,该方法的精度更高。
A new method of wavefront aberration detection based on spatial image adaptive noise reduction is proposed. Through the statistical analysis of the space image, the spatial image noise model and the noise standard deviation model are obtained. Taking the standard deviation of noise as the weighting factor, the principal component analysis (PCA) of the spatial image using the weighted least square method can achieve the adaptive and non-destructive noise reduction of the aerial image, so as to obtain more accurate principal component coefficients and Zernike coefficients. The simulation results of PROLITH using lithography simulation software show that within the 0.1λ aberration amplitude, the accuracy of wavefront aberration detection is improved by more than 30% at the same noise level compared with the wavefront aberration detection technique based on space image principal component analysis. The accuracy of this method is higher in experiments using the lithography experimental platform to measure the Z8 adjustment.