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Use of Genetic Algorithms for Contrast and Entropy Optimization in ISAR Autofocusing

  • Marco MartorellaEmail author
  • Fabrizio Berizzi
  • Silvia Bruscoli
Open Access
Research Article
Part of the following topical collections:
  1. Inverse Synthetic Aperture Radar

Abstract

Image contrast maximization and entropy minimization are two commonly used techniques for ISAR image autofocusing. When the signal phase history due to the target radial motion has to be approximated with high order polynomial models, classic optimization techniques fail when attempting to either maximize the image contrast or minimize the image entropy. In this paper a solution of this problem is proposed by using genetic algorithms. The performances of the new algorithms that make use of genetic algorithms overcome the problem with previous implementations based on deterministic approaches. Tests on real data of airplanes and ships confirm the insight.

Keywords

Entropy Genetic Algorithm Image Contrast Polynomial Model Signal Phase 

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Copyright information

© Martorella et al. 2006

Authors and Affiliations

  • Marco Martorella
    • 1
    Email author
  • Fabrizio Berizzi
    • 1
  • Silvia Bruscoli
    • 1
  1. 1.Department of Information EngineeringUniversity of PisaVia CarusoItaly

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