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논문 기본 정보

자료유형
학술저널
저자정보
Zheng-shuai Jiang (Nanjing University of Posts and Telecommunications) Xin-yang Zhao (Nanjing University of Posts and Telecommunications) Wei Huang (Nanjing University of Posts and Telecommunications) Tao Yang (Nanjing University of Posts and Telecommunications)
저널정보
한국광학회 Current Optics and Photonics Current Optics and Photonics Vol.5 No.3
발행연도
2021.6
수록면
322 - 328 (7page)

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초록· 키워드

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In this paper, a pretreatment method for a matrix in convex optimization is proposed to optimize the spectral reconstruction process of a disordered dispersion spectrometer. Unlike the reconstruction process of traditional spectrometers using Fourier transforms, the reconstruction process of disordered dispersion spectrometers involves solving a large-scale matrix equation. However, since the matrices in the matrix equation are obtained through measurement, they contain uncertainties due to out of band signals, background noise, rounding errors, temperature variations and so on. It is difficult to solve such a matrix equation by using ordinary nonstationary iterative methods, owing to instability problems. Although the smoothing Tikhonov regularization approach has the ability to approximatively solve the matrix equation and reconstruct most simple spectral shapes, it still suffers the limitations of reconstructing complex and irregular spectral shapes that are commonly used to distinguish different elements of detected targets with mixed substances by characteristic spectral peaks. Therefore, we propose a special pretreatment method for a matrix in convex optimization, which has been proved to be useful for reducing the condition number of matrices in the equation. In comparison with the reconstructed spectra gotten by the previous ordinary iterative method, the spectra obtained by the pretreatment method show obvious accuracy.

목차

Ⅰ. INTRODUCTION
Ⅱ. OPERATION PRINCIPLES OF THE SPECTROMETER
Ⅲ. OPTIMIZATION ALGORITHM
Ⅳ. EXPERIMENTAL RESULTS
Ⅴ. CONCLUSION
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