Inverse synthetic aperture radar imaging based on sparse signal processing

Abstract

Based on the measurement model of inverse synthetic aperture radar (ISAR) within a small aspect sector, an imaging method was presented with the application of sparse signal processing. This method can form higher resolution inverse synthetic aperture radar images from compensating incomplete measured data, and improves the clarity of the images and makes the feature structure much more clear, which is helpful for target recognition. The simulation results indicate that this method can provide clear ISAR images with high contrast under complex motion case.

Keywords

ISAR imaging / sparse component analysis / target recognition / high resolution target image