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Remote sensing measurements from space born sensors are strongly attenuated by the scattering and absorption processes through atmospheric molecules, aerosols and gases (ozone, water vapour, oxygen etc). The process of removing the atmospheric interference from the satellite-level signal is called atmospheric correction. Atmospheric correction can be performed through various methods such as, empirical method, semi-physical method, detailed radiative transfer models. Various methods exist for atmospheric correction of available global sensors such as NOAA-AVHRR, MODIS-Terra/Aqua, MERIS, Landsat-TM/ETM etc. However, there was no method available for atmospheric correction of the IRS data sets. A new physics-based model called Scheme for Atmospheric Correction of ResourceSat-2 AWiFS data (SACRS2) has been developed at Space Applications Centre (SAC) specifically tuned for the RS2-AWiFS sensor. This model has been developed from theoretical signal simulations using the 6SV (The Second Simulation of the Satellite Signal in the Solar Spectrum vector version) code. A detail analysis was carried out to perform inter comparison of the results of SACRS2 model with standard atmospheric correction models such as FLAASH (Fast Line-of-sight Atmospheric Analysis of Spectral Hypercube) and 6SV on RS2-AWiFS data. In turn, the performance of all three models was compared to in-situ measurements carried out over an experimental site located in the Kutch desert for seven RS2-AWiFS overpasses. The results showed a fairly good match of reflectance derived by all three correction models with the in-situ measurements.