弱信号亮温光谱的污染气体快速识别算法  

Fast identification algorithm of pollution gas by brightness temperature spectrum of weak signal

作　　者：汪嘉林 熊伟[1] 李大成 吴军 WANG Jialin;XIONG Wei;LI Dacheng;WU Jun(Key Laboratory of Optical Calibration and Characterization,Anhui Institute of Optics and Fine Mechanics,HFIPS,Chinese Academy of Sciences,Hefei 230031,China)

机构地区：[1]中国科学院合肥物质科学研究院安徽光学精密机械研究所,中国科学院通用光学定标与表征重点实验室,安徽合肥230031

出　　处：《大气与环境光学学报》2022年第5期542-549,共8页Journal of Atmospheric and Environmental Optics

基　　金：国家自然科学基金青年科学基金项目,41505020。

摘　　要：基于被动傅里叶变换红外光谱仪设计开发了一种新的快速气体识别算法,利用改进的动量梯度下降法对实测的亮温光谱进行快速的光谱拟合。该方法不需要预先测得背景光谱,能直接从实测光谱中扣除大气气体和天空等背景的干扰,在提取出污染气体成分以及浓度的同时,能实时得到大气中主要气体的浓度程长积,此方法适用于低空背景下弱信号的污染气体识别分析。A new fast gas recognition algorithm was developed based on passive Fourier transform infrared spectrometer,and then the improved momentum gradient descent method was used to realize the fast fitting the measured brightness temperature spectra.This method does not need to measure the background spectrum in advance,and can directly subtract the background interference of atmospheric gas and sky from the measured spectrum.Besides extracting the composition and concentration of the pollutant gas,it can also obtain the concentration-path-length of the main gases in the atmosphere in real time.This method is suitable for the identification and analysis of the pollutant gas with weak signals in the low altitude background.

关 键 词：红外光谱仪 遥感探测 大气污染 气体识别 

分 类 号：P407.1[天文地球—大气科学及气象学]