Frequency-domain-decomposition based white-light interferometry for noise-insensitive measurement

Long Ma; Yuan Zhao; Xin Pei; Fengming Sun; Lei Shi; Yuzhe Liu; Ruijie Qian; Lingxuan Tang; Shengwei Guo

doi:10.1117/12.2601278

9 October 2021 Frequency-domain-decomposition based white-light interferometry for noise-insensitive measurement

Long Ma, Yuan Zhao, Xin Pei, Fengming Sun, Lei Shi, Yuzhe Liu, Ruijie Qian, Lingxuan Tang, Shengwei Guo

Proceedings Volume 11899, Optical Metrology and Inspection for Industrial Applications VIII; 1189904 (2021) https://doi.org/10.1117/12.2601278
Event: SPIE/COS Photonics Asia, 2021, Nantong, JS, China

Abstract

This paper proposed a frequency-domain-decomposition denoising algorithm for nano-scale measurement in white light interferometry (WLI). In this work, the captured correlogram is firstly divided into a series of short-time stationary signals, the phase distribution can then be derived as the sum of the corresponding phase components after Fourier transform. By applying windowed threshold filtering, the noises existed in phase map can be eliminated, and a denoised correlogram is precisely reconstructed. Afterwards, the surface height is retrieved through phase-frequency least-square fitting. In simulations, the phase noises with different levels are investigated. By comparing the noise deviations in the reconstructed phase map with the original one, the effectiveness on noise suppression of the proposed method is properly verified. In the experiments, a height step standard with calibrated values 182±2.0nm are tested, where the height deviations below 3nm and the repeatability of 0.5% has proved the robustness of our proposed method.

Citation Download Citation

Long Ma, Yuan Zhao, Xin Pei, Fengming Sun, Lei Shi, Yuzhe Liu, Ruijie Qian, Lingxuan Tang, and Shengwei Guo "Frequency-domain-decomposition based white-light interferometry for noise-insensitive measurement", Proc. SPIE 11899, Optical Metrology and Inspection for Industrial Applications VIII, 1189904 (9 October 2021); https://doi.org/10.1117/12.2601278

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