Foliage-concealed Target Discrimination Of UWB SAR Based On ROI

Ultra-Wide Band Synthetic Aperture Radar (UWB SAR) is usually used to detect the foliage-concealed targets as is important in military application. The research of UWB SAR target discrimination can improve the application value of UWB SAR. The shortages of isolated angle and deficient systematism exist in the discussion about it in reference. This paper tries to overcome above shortages, surrounds a main clue of Region of Interest (ROI) tightly and investigates the important techniques in UWB SAR target discrimination systemically.The ROI extraction in foliage clutter is investigated. The problems, which appear when a two-parameter Constant False Alarm Rate (CFAR) detector and an intelligent CFAR detector are used in foliage clutter, are analyzed. The median filter is proposed to be used to solve above problems. The performances of three median filters are investigated and compared from four aspects. The problems, which appear when the common cluster algorithm is used in foliage clutter, are analyzed. In order to solve above problems, the first means is to improve the common cluster algorithm, and the second means is to adopt a morphological filter. Both means can improve the cluster results in foliage clutter effectively. A quick and effective extraction approach of ROI suitable in foliage clutter is proposed.The single-scale feature extraction of ROI in UWB SAR image is investigated. The validities of amplitude features and their extraction method suitable in high-frequency SAR image are analyzed when they are used in UWB SAR image. An extraction approach of amplitude feature based on target contour is presented, and the corresponding effective amplitude features are proposed. The old dihedral angle model is analyzed and improved. The approach of azimuthal feature extraction is proposed based on the conclusion of the improved dihedral angle model. The problems, which appear when the common change detection methods are used to extract the change feature based on ROI, are analyzed. And a robust and feasible extraction approach is presented.The multiscale feature extraction of ROI in UWB SAR image is investigated. The applicabilities of multiresolution feature extraction methods suitable in high-frequency SAR image are analyzed when they are used in UWB SAR image. The equivalent scattering models of trunk clutter and target are established, and the differences of multiresolution characteristic between trunk clutter and target are analyzed. Two effective multiresolution feature extraction approaches are proposed based on real and complex images respectively.The classifier design and the performance evaluation in UWB SAR target discrimination are investigated. Two kinds of classifiers in common use are summarized. The parameter system suitable for performance evaluation of UWB SAR target discrimination is consummated. A process evaluation approach is proposed to evaluate the discrimination performance of UWB SAR target discrimination algorithm step by step. An evaluation approach based on polynomial fitting is proposed to evaluate the robustness performance of UWB SAR target discrimination algorithm.Finally, the research prospect in future is proposed based on the study summary of full paper.