光学学报, 2019, 39 (9): 0930007, 网络出版: 2019-09-09
基于小波变换的干涉光谱信号检测与校正方法 下载: 1025次
Detection and Revision of Interference Spectral Signals Based on Wavelet Transforms
光谱学 傅里叶变换光谱仪 干涉条纹检测 小波变换 spectroscopy Fourier transform spectrometer interference fringe test wavelet transform
摘要
傅里叶变换光谱仪通过获取待测光的干涉信号来反演光谱信息,是重要的光谱测试与分析仪器。受光电探测电路不稳定、干涉模块装调不到位等因素的影响,傅里叶变换光谱仪获得的干涉光谱信号会出现漏采点、过饱和点、噪声点等无效数据点,导致反演的光谱信号出现失真。为此,研究了一种基于小波变换的干涉光谱信号检测方法,该方法能够快速有效地定位干涉信号中多种无效数据点的位置;在此基础上,研究了干涉光谱信号的校正方法,根据无效点所在区间段的信号特征,通过样条插值方法进行数据拟合,校正干涉光谱信号。通过仿真验证了本方法的可行性;搭建了近红外波段傅里叶变换光谱实验系统,并基于该系统进行验证性实验,对获得的干涉信号进行检测与校正,提高了反演光谱信号的准确性。
Abstract
Fourier transform spectrometry is an important device in spectral testing and analysis, which reconstructs a spectrum from a captured interference spectral signal. Invalid data points of the interference spectral signal, such as missing sampling points, oversaturation points, and noise points, arise from the photoelectric detection circuit’s instability and inadequate installation of interference module, and the recovery spectrum from an interference spectral signal containing such invalid data points causes distortion. Hence, a method for testing interference spectral signals is proposed using wavelet transforms, wherein invalid data points are quickly and effectively located, and a method for revising the interference spectral signal is researched based on interference signal characteristics of the interval where invalid data points are located. Spline interpolation is used for data fitting, and the interference spectral signal is revised accordingly. The feasibilities of both proposed methods are verified via simulation, and they are validated using a near-infrared Fourier transform spectrometer prototype. Thus, interference signals of the prototype are tested and revised to improve the accuracy of the recovery spectral signal.
孟鑫, 刘磊, 江升, 张冰, 李志增. 基于小波变换的干涉光谱信号检测与校正方法[J]. 光学学报, 2019, 39(9): 0930007. Xin Meng, Lei Liu, Sheng Jiang, Bing Zhang, Zhizeng Li. Detection and Revision of Interference Spectral Signals Based on Wavelet Transforms[J]. Acta Optica Sinica, 2019, 39(9): 0930007.