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An Improved Scheme for Target Discrimination in High-Resolution SAR Images

机译:一种高分辨率SAR图像中目标识别的改进方案

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摘要

To design a highly automatic and practical method for target discrimination in synthetic aperture radar images, we propose in this paper an improved scheme consisting of the framework and algorithms for target discrimination. Our main contribution in this scheme comprises four aspects. First, an integrative frame sequentially combining the algorithm based on feature extraction and the knowledge of target group has been presented. Second, three new features for target discrimination have been introduced. Third, a genetic algorithm-based feature-selection algorithm has been presented. The results show that this algorithm can evaluate the goodness-of-feature better. Finally, to improve the accuracy of the discriminator, we have designed a weighted quadratic distance discriminator, which has been observed to improve the performance of target discrimination. We have analyzed the performance of the proposed scheme comprehensively and specifically using some measured data, and carried out comparisons of the existing algorithms. The results show that the proposed scheme could improve the application ability in target discrimination.
机译:为了设计合成孔径雷达图像中目标识别的一种高度自动化和实用的方法,我们在本文中提出了一种改进的方案,该方案包括目标识别的框架和算法。我们对该计划的主要贡献包括四个方面。首先,提出了一种综合框架,该框架依次结合了基于特征提取的算法和目标群体的知识。第二,引入了目标识别的三个新功能。第三,提出了一种基于遗传算法的特征选择算法。结果表明,该算法可以更好地评价特征优度。最后,为了提高鉴别器的准确性,我们设计了加权二次距离鉴别器,已观察到它可以提高目标鉴别的性能。我们已经使用一些实测数据全面,具体地分析了该方案的性能,并对现有算法进行了比较。结果表明,该方案可以提高目标识别的应用能力。

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