Remote trace gas quantification using thermal IR spectroscopy and digital filtering based on principal components of background scene clutter

For many years Hughes Danbury Optical Systems has been developing algorithms for detecting trace gases in the atmosphere using hyper-spectral data processing techniques. We have shown in the past that our Orthogonal Background Suppression (OBS) algorithms are effective for measuring the column density-thermal radiance contrast product of a gas plume in the atmosphere at some distance from a passive thermal-IR emission spectrometer. The algorithm facilitates the detection of the target signal in the presence of low signal to spectral clutter ratio. Our current work shows that using the non-linear absorption features of a target gases' spectral signature, coupled with our OBS algorithm, we can separate column density-thermal radiance contrast product and obtain absolute plume column density and plume temperature. The OBS algorithms are straight forward and allow detection near theoretical random noise limits. The efficacy of our novel technique is demonstrated using simulations and field data.