• DocumentCode
    1254418
  • Title

    Model-based neural network for target detection in SAR images

  • Author

    Perlovsky, Leonid I. ; Schoendorf, William H. ; Burdick, Bernard J. ; Tye, David M.

  • Author_Institution
    Nichols Res. Corp., Lexington, MA, USA
  • Volume
    6
  • Issue
    1
  • fYear
    1997
  • fDate
    1/1/1997 12:00:00 AM
  • Firstpage
    203
  • Lastpage
    216
  • Abstract
    A controversial issue in the research of mathematics of intelligence has been that of the roles of a priori knowledge versus adaptive learning. After discussing mathematical difficulties of combining a priority with adaptivity encountered in the past, we introduce a concept of a model-based neural network, whose adaptive learning is based on a priori models. Applications to target detection in SAR images are discussed. We briefly overview the SAR principles, derive relatively simple physics-based models of SAR signals, and describe model-based neural networks that utilize these models. A number of real-world application examples are presented
  • Keywords
    adaptive signal processing; learning (artificial intelligence); neural nets; radar detection; radar imaging; synthetic aperture radar; SAR images; a priori knowledge; adaptive learning; model-based neural network; physics-based models; real-world application; target detection; Adaptive systems; Artificial intelligence; Artificial neural networks; Biological neural networks; Intelligent networks; Learning; Mathematical model; Neural networks; Object detection; Target recognition;
  • fLanguage
    English
  • Journal_Title
    Image Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1057-7149
  • Type

    jour

  • DOI
    10.1109/83.552107
  • Filename
    552107