This thesis offers an extensive assessment of “space-time adaptive processing” (STAP and knowledge-aided STAP (KA STAP) for airborne radar. The topic is handles from both theoretical and intuitive contexts. A main prerequisite of space-time adaptive processing is information of the spectral features under the scenario of interference. Nonetheless, these are occasionally recognised actually and should be assessed by means of training data (TD). The TD collection in a particular situation is restricted by the extent of change of the phenomenon of interference regarding time and space along with the system concerns like bandwidth. Progressively multifaceted scenarios of interference produce demanding circumstances of training support and the TD choice turns out to be a vital part of the “adaptive process”. Further matters of significance in space-time adaptive processing comprise the adaptive algorithm computational cost in addition to the capacity to uphold a constant false rate of alarm over extensively changing “interference statistics”. This thesis handles these matters, establishing the necessity for a KA viewpoint.
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