Ground Moving Target Detection Using Multi- Features under Antenna Array Crabbing
This paper introduces a new moving target detection method under crabbing error due to platform motion. Two contour-based attributes known as circularity ratio and bending energy are extracted to a transformed domain of the radar samples. These features are applied to detect the target and non-linear clutter using a machine learning classifier. The effectiveness of the contour-based features is validated with simulation results.
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