Radar Systems are used for the detection of objects by transmitting the electromagnetic waves in the free space. They operate in environments where there is a high possibility that the desired echo signal interferes with the signals from other sources. These signals include clutters and jammer signals. The jammer is a device that continuously emits the wideband radio signals in the radar environment, to saturate the receiver with noise or false information. Thus, the total received signal has three components- returns from target, clutter, and jammer combined i.e. it is a three dimensional signal. The use of conventional signal processing techniques is not desirable, as they cannot separate the desired echo signal from the other components, because the statistics of these components present in the received signal is not known. This problem needs to be accounted for, in airborne surveillance radars, as they have to identify and locate the targets in multiple interference environments. The Space-Time Adaptive Techniques (STAP) is a combination of spatial and temporal filtering that can nullify the jammer signal, and recognize the slow-moving targets. These techniques filter the signal in the angular and the Doppler domain for suppressing the unwanted signals. This paper presents a theoretical study of space-time adaptive coding techniques, and the MATLAB implementation of STAP algorithms; namely, SMI, DPCA, and ADPCA, to suppress clutter and jammer interference in the received pulse.