Abstract
The Knowledge-Aided Sensor Signal Processing and Expert Reasoning (KASSPER) program aims to improve airborne ground moving target indicator (GMTI) radar performance by taking into account all available prior knowledge. One powerful piece of information is that the radar return signal is a superposition of near-ideal plane-waves. A plane-wave signal and clutter model or sampled GMTI radar data can be used to calibrate the receive array, suppress clutter, and detect moving targets. Each range gate is processed independently. Sample covariance matrices are unnecessary. The synthetic KASSPER challenge datacube is processed to demonstrate performance.
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