ISAR motion detection and compensation using genetic algorithms

Based on the point scatterer model, a radar signal can be effectively analyzed using the joint time-frequency (JTF) method. The basis functions of a few prominent point scatterers are believed to carry target motion information essential to the ISAR imaging process. One major problem with the JTF method is the computation load associated with the exhaustive search process for motion parameters. In this paper, genetic algorithms (GA) are used to for the parameterization process in the JTF method. Real and binary coded GA are investigated and their performance compared with the exhaustive search. It is shown that a significant amount of time can be saved while achieving almost the same image quality by using real-coded GA.