大部分污染气体在红外波段具有明显的发射或吸收特征，被动傅里叶变换红外(FTIR)遥感技术可以对污染气体进行远距离探测和识别。当利用移动平台对污染气体进行遥测时，背景辐射是未知的，且光谱中包含大气等干扰物特征，需要研究相应的背景压缩方法，提取目标光谱特征。研究了基于亮温光谱的红外背景压缩方法，认为背景辐射在亮温光谱上是缓变的基线，并利用中光谱分辨率大气辐射传输模型(MODTRAN)软件包模拟大气干扰物特征，根据最小二乘拟合原理实现红外背景压缩。实验以氨气作为目标气体，以低平天空作为背景。结果表明，本方法能够成功扣除背景辐射和大气干扰特征，提取氨气的光谱特征，并计算了氨气的浓度程长积值。

Most pollutant gases have obvious absorbing or emitting features in the infrared band. Passive Fourier transform infrared (FTIR) remote sensing technology is used to detect and identify pollutant gases in a standoff distance. In the case of remote sensing pollutant gases on the mobile platform, the background is unknown and the spectrum includes interferents′ spectral features such as atmospheric gases, thus background compression method is needed to extract target spectral features. An infrared background compression method based on brightness temperature spectrum is proposed, in which the background radiance is referred as a slowly-varied baseline. The radiance transmitting simulation software named MODTRAN is used to simulate interferents′ spectral features such as atmospheric gases, and the infrared background compression is realized based on least-square fitting principle. The experiment takes ammonia as the target gas and the low altitude sky as the background. The results indicate that this method can effectively compress the background and interferents′ features, extract the ammonia′s spectral features and calculate the concentration-path-length.