Space Time Adaptive Processing (STAP) is a multi-dimensional adaptive signal processing technique, which processes the signal in spatial and Doppler domains for which a target detection hypothesis is to be formed. It is a sample based technique and based on the assumption of adequate number of Independent and Identically Distributed (i.i.d.) training data set in the surrounding environment. The principal challenge of the radar processing lies when it violates these underlying assumptions due to severe dynamic heterogeneous clutter (hot clutter) and jammer effects. This in turn degrades the Signal to Interference-plus-Noise Ratio (SINR), hence signal detection performance. Classical Wiener filtering theory is inadequate to deal with nonlinear and nonstationary interferences, however Wiener filtering approach is optimal for stationary and linear systems. But, these challenges can be overcome by Adaptive Sequential State Estimation (ASSE) filtering technique.