Abstract:

The heterogeneity of echo data in airborne radar can severely degrades the clutter suppression performance of conventional spacetime adaptive processing (STAP)algorithms. To address this issue, a heterogeneous clutter suppression method based on the prior knowledge of clutter ridges is presented. A set of steering vector basis is first constructed by utilizing the spectral characteristics of the ground clutter seen by airborne radar, and then used to fit the test data in an iterative least meansquare manner with the presence of the array error under consideration. Subsequently,  the constant false alarm rate detection is conducted on the residual data. This method makes full use of the prior knowledge of radar system parameters and clutter spectral structure and does not need any training samples, which can effectively suppress the heterogeneous clutter and significantly improve the detection performance of the airborne radar. Simulation results validate the effectiveness of the proposed method.