Supervised Self-Organizing Classification of Superresolution ISAR Images: An Anechoic Chamber Experiment

@article{Radoi2006SupervisedSC,
  title={Supervised Self-Organizing Classification of Superresolution ISAR Images: An Anechoic Chamber Experiment},
  author={Emanuel Radoi and Andr{\'e} Quinquis and Felix Totir},
  journal={EURASIP J. Adv. Sig. Proc.},
  year={2006},
  volume={2006}
}
The problem of the automatic classification of superresolution ISAR images is addressed in the paper. We describe an anechoic chamber experiment involving ten-scale-reduced aircraft models. The radar images of these targets are reconstructed using MUSIC-2D (multiple signal classification) method coupled with two additional processing steps: phase unwrapping and symmetry enhancement. A feature vector is then proposed including Fourier descriptors and moment invariants, which are calculated from… CONTINUE READING
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