Joint super-resolution moving target feature extraction and stationary clutter suppression

High range resolution (HRR) moving target indicator radar is becoming increasingly important for many military and civilian applications involving the detection and classification of moving targets within a clutter background. For ground-based HRR radar, when targets are moving slowly or near-broadside and the coherent processing interval or dwell time is not too long, the effects of range migration and range feature distortion can be ignored. Based on this assumption, relaxation-based algorithms that are robust and computationally simple are proposed for HRR feature extraction of moving targets consisting of scatterers closely spaced in range in the presence of stationary clutter. Numerical examples show that the proposed algorithms exhibit super-resolution and excellent estimation performance