Target Discrimination and Classification in Through-the-Wall Radar Imaging

In this paper, a scheme for target discrimination and classification is proposed. The proposed scheme is applied to through-the-wall microwave images obtained by using a wideband radar implementing frequency-domain back-projection. We consider stationary targets where Doppler and change-detection based techniques are inapplicable. The proposed scheme applies image segmentation, followed by feature extraction. We map target returns to a feature space, where discrimination among different targets and clutter is performed. To achieve target-clutter discriminations independent of target location in range and cross-range, we use compensation methods to account for varying system resolution within the perimeter of the scene imaged. Real data collected using an indoor radar imaging scanner is used for validation of performance.

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