A multi-scale narrow band correlated-k distribution (MSNBCK) model is developed to simulate infrared radiation (IR) from an exhaust system of a typical aircraft engine. In this model, an approximate approach instead of statistically uncorrelated assumption is used to treat overlapping bands in gas mixture. It significantly reduces the requirement for computing power through converting the exponential increase of computing power consumption with the increase of participating gas species to linear increase. Besides, MSNBCK model has a great advantage compared with conventional methods which can estimate each species’ contribution to the total gas mixture radiation intensity. Line by line (LBL) results, experimental data and other results in the references are used to evaluate this new model, which demonstrates its advantage in terms of accuracy and computing efficiency. By coupling this model and finite volume method (FVM) into radiative transfer equation (RTE), a comparative study is conducted to simulate IR signature from the exhaust system. The results indicate that wall’s IR emission should be considered in both 3–5 μm and 8–14 μm bands while gases’ IR emission plays an important role only in 3–5 μm band. For plume IR radiation, carbon dioxide’s emission is much more significant than that of water vapor in both 3–5 μm and 8–14 μm bands. Especially in 3–5 μm band, the water vapor's IR signal can even be neglected compared with that of carbon dioxide.