应用主成分分析评估红外高光谱仪器噪声特性  

Noise Estimation of Hyper-spectral Infrared Atmospheric Sounder Observations Using Principal Component Analysis

作　　者：李路 漆成莉[1] 张鹏[1] 胡秀清[1] 顾明剑[2] LEE Lu;QI Cheng-li;ZHANG Peng;HU Xiu-qing;GU Ming-jian(Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites,National Satellite Meteorological Centre,Beijing 100081,China;Shanghai Institute of Technical Physics,Chinese Academy of Sciences,Shanghai 200083,China)

机构地区：[1]国家卫星气象中心中国遥感卫星辐射测量和定标重点开放实验室,北京100081 [2]中国科学院上海技术物理研究所,上海200083

出　　处：《光子学报》2019年第2期148-156,共9页Acta Photonica Sinica

基　　金：国家自然科学基金(No.41505029)~~

摘　　要：为了考察星载傅里叶变换光谱仪观测实际目标时的噪声水平,研究了通过大气观测光谱的虚部分量估计噪声的方法.采样误差等因素会给虚部光谱样本引入通道相关性噪声,并叠加在固有随机噪声分量上,从而抬升总体噪声水平,甚至超出灵敏度指标.采用主成分分析技术重构相关噪声分量,将两类噪声相互分离.将主成分分析滤出的随机噪声与由定标源光谱统计的噪声进行对比,结果显示,仪器观测不同目标的随机噪声相互一致,并且在三个工作波段均分别满足0.4K、0.7K和1.2K的灵敏度设计指标.To evaluate the noise during atmosphere observation,the imaginary part of the atmospheric complex Fourier transform spectra are taken into consideration.However,the imaginary spectrally correlated noise introduced by sampling jitters would be added to the random noise inherent to infrared detectors,which elevates the total instrumental noise floor or even exceeds the sensibility threshold.Utilizing principal component analysis technique,this correlative noise could be reconstructed and filtered out.Then the remaining noise is represented as the noise equivalent differential temperature and compared with that from the calibration target radiance.The results show that the random spectra noises from different scenes are consistent with each other,and all meet the sensibility requirments of 0.4 K,0.7 K and 1.2 K corresponding to three spectral bands.

关 键 词：红外高光谱 傅里叶变换光谱仪 噪声等效温差 主成分分析 随机噪声 

分 类 号：O433.1[机械工程—光学工程] TH765[理学—光学]