Use of genetic algorithm for ISAR image autofocusing
Marco Martorella - University of Pisa, Fabrizio Berizzi - University of Pisa, Silvia Bruscoli - University of Pisa
Tue, 27 April 2004, 4:10 PM - 5:30 PM
One of the most critical steps of ISAR image processing is the motion compensation, also known as ISAR image focusing. For non-cooperative targets and especially when external data are not available, autofocusing techniques must be used. Among all the techniques developed for ISAR image autofocusing, the Contrast Based Autofocusing Technique has been lately proposed by the authors. One of the critical aspects of such a technique is represented by the solution of an optimisation problem. Because the Image Contrast is generally a multimodal function, classic optimisation methods do not reach the best result. In this paper a new solution of the optimisation problem is given by means of genetic algorithms. Moreover, the model of the focusing point phase history is extended to a generic polynomial and the problem of defining the polynomial order is addressed and heuristically solved. The effectiveness of the algorithm improvements, due to both the use of genetic algorithms and to the signal model extension is tested by means of real data.
Dr Marco Martorella - University of Pisa
Marco Martorella received Laurea Degree (cum laude) and Ph.D. at the University of Pisa, respectively in 1999 and 2003. He is currently working at the Dept. of Information Engineering of the University of Pisa as researcher. His areas of interests cover ISAR autofocusing and image formation and Radar Remote Sensing.