This paper proposes an efficient method to classify inverse synthetic aperture radar (ISAR) images. The proposed method achieves invariance to translation and rotation of ISAR images by using two-dimensional (2D) Fourier transform (FT) of ISAR images, polar mapping of the 2D FT image, and a simple nearest-neighbor classifier. In simulations using ISAR images measured in a compact range, the proposed method yielded high classification ratios with small-sized data regardless of the location of the rotation center, whereas the existing method was very sensitive to the location of it.
Efficient classification of ISAR images using 2d fourier transform and polar mapping
IEEE Transactions on Aerospace and Electronic Systems ; 51 , 3 ; 1726-1736
2015-07-01
2114184 byte
Article (Journal)
Electronic Resource
English
Nonlinear feature extraction applied to ISAR images of targets for classification
Tema Archive | 2001
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