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Research on SAR images recognition based on ART2 neural network

  • Xiaoming Ye*
  • , Wei Gao
  • , Yi Wang
  • , Xiaoguang Hu
  • *Corresponding author for this work
  • Beihang University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

ART2 is a kind of self-organizing neural network which is based on adaptive resonance theory. It carries out the recognition by using competive learning and self-steady mechanism, and can learn by itself in dynamic environment with noise and without supervision. Its learning process can recognize learned models fastly and be adapted to new unknown objects rapidly. SAR ATR (Synthetic Aperture Radar Automatic Target Recognition) approach based on PCA and ART2 neural network is proposed in this paper. It takes the principal components as sample features, and then ART2 neural network is used to recognize SAR images. Experimental results with MSTAR SAR data sets show a better performance of recognition and generalization.

Original languageEnglish
Title of host publicationProceedings of the 2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012
Pages1888-1891
Number of pages4
DOIs
StatePublished - 2012
Event2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012 - Singapore, Singapore
Duration: 18 Jul 201220 Jul 2012

Publication series

NameProceedings of the 2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012

Conference

Conference2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012
Country/TerritorySingapore
CitySingapore
Period18/07/1220/07/12

Keywords

  • ART2 neural network
  • PCA
  • SAR
  • recognition

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