Clutter suppression for multichannel wide area surveillance system via a combination of STAP and RPCA

Wide area surveillance ground moving target indication (WAS-GMTI) is an important mode of multichannel airborne radar. Space-time adaptive processing (STAP) is widely used in WAS-GMTI clutter suppression. However, it will be difficult to estimate the clutter plus noise spectral density matrix accurately when the training samples are contaminated by moving targets. In this paper, target-free training samples obtained via robust principal component analysis (RPCA) algorithm are used for more accurate clutter plus noise spectral density matrix estimation. An eigenvector subspace projection method is used to calculate the filter vector. The simulation results show the advantages of the proposed method.