A generalized sample weighting method in heterogeneous environment for space-time adaptive processing

In the heterogeneous clutter and target rich environments, the conventional statistical space-time adaptive processing (STAP) methods are confronted with the problem of the lack of valid training samples, which may result in the performance degradation in clutter rejection. Thus, in this paper, a generalized sample weighting method in angle-Doppler domain (GSWADD) is presented and hence an implementation of STAP based on GSWADD. Firstly, the angle-Doppler spectrum of common clutter is estimated by means of the local weighting coefficients, measured according to the distinctions between the clutter and moving targets in the angle-Doppler plane along the range gate, where moving targets are sparse while clutter are dense. Then, the reconstructions of clutter-plus-noise covariance matrix (CCM) without aperture loss and subsequently clutter suppression are carried out. Finally, the results of the experiments based on simulated and real measured data demonstrate that the proposed method can effectively alleviate the STAP performance degradation resulting from the loss of training samples contaminated by the interference targets, compared with the conventional statistical STAP algorithms.