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被动傅里叶变换红外(FTIR)遥感是一种具有应用潜力的生物气溶胶远程探测技术。红外遥感测量中目标光谱特征上往往存在噪声信号和基线漂移。而生物气溶胶的光谱特征相对较宽,传统的基线校正方法都不适用。由于生物气溶胶红外光谱和不同形式的基线漂移都是非高斯信号,把非高斯性作为独立性度量,基于独立成分分析(ICA)技术设计了生物气溶胶红外光谱信号的预处理算法。试验结果表明,该算法可以把未知干扰成分、基线漂移等作为独立分量分离出来,从而不影响进一步的定性、定量分析。
Passive Fourier transform infrared (FTIR) remote sensing is a bio-aerosol remote detection technology with potential applications. Infrared remote sensing measurement of the target spectral characteristics often exist noise signal and baseline drift. However, the spectral characteristics of bio-aerosol are relatively wide, and the traditional baseline correction methods are not applicable. Because bio-aerosol infrared spectra and different forms of baseline drift are non-Gaussian signals, the non-Gaussianity is taken as the measure of independence and the pretreatment algorithm of bio-aerosol infrared spectrum signal is designed based on Independent Component Analysis (ICA). Experimental results show that this algorithm can separate unknown interference components and baseline drift as independent components, so as not to affect further qualitative and quantitative analysis.