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Target Discrimination Based on High-Resolution SAR Images

Hongfu Wang, Xiaorong Xue


With the aim of designing a highly automatic and practical process of target discrimination for SAR images, this research has proposed an improved scheme consisting of the framework and algorithms for target discrimination. The paper mainly includes 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. 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 algorithm could improve the application ability in target discrimination.


Genetic algorithm, synthetic aperture radar, target discrimination, quadratic distance discriminator, weighted quadratic distance discriminator.

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