Abstract:

To solve the problem that the traditional space-time adaptive and processing method cannot effectively suppress the heterogeneous clutter due to lack of enough independent identically distributed training samples, an iteration-separable clutter suppression algorithm for airborne planar array radar is proposed. Firstly, the clutter representation basis matrix is constructed based on some priori information such as radar system and aircraft platform motion parameters. Then, the spatial and temporal clutter power spectrum of cell under test (CUT) are separately estimated by the covariance matching estimation criterion. Next, the spatial and temporal partial weights are calculated through the linearly constrained minimum variance criterion. Finally, combined with the clutter parameterized model and the obtained spatial and temporal partial weight vectors, the space-time filtering weight vector is calculated to process the CUT echo data. The proposed method is hyperparameter-free, which is global convergent and does not need the training samples. In addition, the proposed method can effectively suppress the heterogeneous clutter of echo data of airborne planar array radar even if range ambiguity exists. Simulation results demonstrate the effectiveness of the proposed method.

Key words: airborne planar array radar, heterogeneous clutter, clutter suppression, space-time adaptive processing