Polarization-Space-Time Adaptive Processing for Clutter Suppression in Airborne Radar Systems

Clutter suppression is the serious problem for airborne surveillance radar systems. The paper analyses polarization-space-time (PST) joint domain adaptive processing technique for clutter suppress. Firstly, the received target signal model was established in the case of completely polarized wave. Secondly, the optimal weighted vector is obtained using the maximal outputting SINR principle. Then, a new technique, with spectral analysis and resolution grid, is utilized for deriving performance of clutter suppression. We demonstrate that the main factors which are affect on the performance of clutter rejection, i.e. the clutter degree of polarization, statistical spherical distance of Poincare sphere between target and clutter, Doppler frequency of target and input clutter and noise ratio. Finally, compared to STAP, the performance of polarization-space-time adaptive processing (PSTAP) is significantly better, especially in the case of a target slowly or tangentially moving. The simulation verifies the model correctness and conclusions.