The application of motion compensation of ISAR image for a moving target in radar target recognition

Abstract

Inverse synthetic aperture radar (ISAR) is an imaging technique which generates a two-dimensional (2D) high resolution image of a target. In general, ISAR image is often adequate to discriminate various missiles, military aircraft, and civilian aircraft and so on. However, if the target has complicated motion such as pitching, yawing, rolling, and maneuvering, ISAR image is not enough to classify, among these targets. This article presents high resolution techniques for application in motion compensation of ISAR image for a radar backscattered signal from the moving target. A simple Fourier Transform (FT) is employed to obtain ISAR image for a moving target, then the image is usually blurred. These images blurring problem can be solved with the time-frequency transform. In this article, we compensate the translational motion using the minimum entropy method (MEM) and rotational motion using the Gabor Wavelet Transform (GWT) for a moving target. To show, the performances of each technique, we use backscattered field data of the ideal point scatterers and the simulated MIG-25 to obtain motion compensated ISAR image and display the resolution of motion compensated ISAR images. (c) 2008 Wiley Periodicals, Inc.