被动傅里叶变换红外遥测技术可以测量大部分污染气体,亮温光谱法能够在无需背景信息的前提下实现目标特征提取与识别。在野外进行实测时, 存在背景物体辐射、大气中成分辐射、仪器噪声等信号。当目标信号弱于这些信号时,亮温光谱法难以直接从实测光谱中提取目标特征。 针对这一问题,提出了一种基于非负矩阵分解的光谱特征提取方法,在被动红外遥测模型基础上,通过对整个亮温光谱进行分析,得到目标光谱特征。 实际测量以SO2为目标气体进行野外实验,对该方法进行了验证,结果表明,在目标信号较弱的亮温光谱中仍然能够提取到SO2的光谱特征,证明了方法的有效性。

Most pollutant gases can be detected by passive Fourier transform infrared(FTIR) remote sensing technique, and brightness temperature technique can implement the extraction and identification of target feature without the premise of background information. There usually exist radiation of background objects, radiance of atmospheric composition, and noise from the instrument itself in field measurements. When the target signal is weaker than these signals, the target feature can’t be extracted directly from the measured spectra by the brightness temperature technique. Accordingly, an extraction method of spectra feature from measured spectra based on non-negative matrix factorization(NMF) is proposed. It can get the target feature through the analysis of the brightness spectra on the basis of passive Fourier transform infrared remote sensing. The experiment is conducted with SO2 as the target gas. The method is verified with the measured spectra. Results show that the feature of SO2 can be extracted even if the target signal is weak. The validity of the method is proved.