Windowed Two-Dimensional Fourier Transform Concentration and Its Application to ISAR Imaging

This paper presents a novel non-parametric technique for two-dimensional spectrum readability enhancement. The approach is based on relocating a windowed bivariate Fourier transform with regard to its frequency estimates computed using a moving analyzing window. To this aim, four spatial instantaneous frequency estimators are proposed. A strongly concentrated spectrum with improved component separability is obtained with the proposed technique. The method was intensively tested using simulated and real-life signals. As an example of the method application, inverse synthetic aperture radar (ISAR) images were created and then focused, significantly improving the contrast and entropy. However, the presented technique can be applied to other bivariate signal analyses whenever the windowed two-dimensional Fourier transform (W2D-FT) is applied.