EURASIP Journal on Applied Signal Processing 
Volume 2006 (2006), Article ID 87298, 11 pages
doi:10.1155/ASP/2006/87298

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

Marco Martorella, Fabrizio Berizzi, and Silvia Bruscoli

 Department of Information Engineering, University of Pisa, Via Caruso, Pisa 56126, Italy
Received 4 May 2005; Revised 25 October 2005; Accepted 21 December 2005

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.