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12 September 2003 Robustness of features for automatic target discrimination in high-resolution polarimetric SAR data
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We have studied the robustness of features against aspect variability for the purpose of target discrimination using polarimetric 35 Ghz ISAR data. Images at a resolution of 10 cm and 30 cm have been used for a complete aspect range of 360 degrees. The data covered four military targets: T72, ZSU23/4, T62, and BMP2. For the study we composed several feature vectors out of individual features extracted from the images. The features are divided into three categories: radiometric, geometric and polarimetric. We found that individual features show a strong variability as a function of aspect angle and cannot be used to discriminate between the targets irrespectively of the aspect angle. Using feature vectors and a maximum likelihood classifier reasonable discrimination (about 80%) between the four targets irrespective of the aspect angle was obtained at 10 cm resolution. At 30 cm resolution less significant discrimination (less than 70%) was found irrespective of the kind of feature vector used. In addition we investigated target discrimination per 30-degree aspect interval. In order to determine the aspect angle of targets we used a technique based on the Radon transformation, which gave an accuracy of about 5 degrees in aspect angle. We found that in this case good discrimination (more than 90%) was obtained at 10 cm resolution and reasonable discrimination (about 80%) at 30 cm resolution. The results are compared with analogous results from MSTAR data (30 cm resolution) of comparable targets.
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Albertus C. van den Broek, Rob J. Dekker, and Phillippe Steeghs "Robustness of features for automatic target discrimination in high-resolution polarimetric SAR data", Proc. SPIE 5095, Algorithms for Synthetic Aperture Radar Imagery X, (12 September 2003);

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