Extension of applications of sonar from deep water to shallow and very shallow water cause sonar designers to create special techniques in order to overcome underwater acoustic channel challenges in shallow water. In such environments reverberation is dominant limiting effect and is a severe problem for active sonar, because the target echo level may not exceed the reverberation level and so the performance of active sonar detector will be degraded. The problem becomes more challenging if the sonar platform is moving, producing self-induced Doppler spread in reverberation. In other hand, corresponding Doppler frequency of targets with slow relative speeds is low. So the target Doppler frequency falls in the region of reverberation spectrum. In these situations, conventional techniques such as matched filtering are inefficient leading to the degradation of the detection performance of active sonar, therefore special techniques that process signals in both spatial and temporal dimension will be required. Such techniques suppress reverberation and improve the detection performance. In this thesis, space time adaptive processing (STAP) techniques for detection of slow targets in active sonar with moving platform, is studied and simulated. Sub-optimum techniques introduced to overcome some Limitations of fully adaptive space time processor. According to the characteristics of underwater acoustic channel, it is obvious that there are major differences between propagation of acoustic waves under water and electromagnetic waves in the air. These differences cause severe limitations in using STAP for sonar. The final goal of this thesis is to investigate these limitations and propose a new approach to overcome that. Simulation results show that proposed technique is useful in real underwater conditions and highly suppress reverberation without conventional STAP limitations. Keywords: STAP, Active Sonar, Reverberation, Detection