A reduced rank STAP with change of PRF

The effect of the PRF on the performances of the reduced rank STAP is discussed. The numerical evaluation is based on three different models of changing the PRF, namely quadratic, pseudorandom and chaotic with two methods of reduction of the rank: Principle Components (PC) and Signal to Interference Noise Ratio (SINR metric). Rank reduction reduces the computing time and cost. The simulation results show that the change of PRF solves well the problem of ambiguities while using a reduced rank of covariance matrix of the environment. Also, a comparative study shows that the chaotic change is better and this is due to the simplicity of the generation of the impulses on one hand while basing itself on simple electronic circuits, such as the circuit of Chua, and on the other hand, the possibility of taking a large variety of PRFs at the same time. In fact, we use the properties of a chaotic system, to sweep all the space.