Efficient Classification of ISAR Images

K.-T. Kim (Korea)


ISAR, target classification, radar, feature extraction


In this paper, we propose a method to classify inverse syn thetic aperture radar (ISAR) images from different targets. Our approach can provide efficient features for classifica tion by the combined use of a polar mapping procedure and a well-designed classifier. The resulting feature vec tors are able to meet the requirements that efficient features should have: invariance with respect to rotation and scale, small dimensionality, as well as highly discriminative in formation. Typical experimental examples of the proposed method are provided and discussed.

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