This paper presents an innovative Compressive Sensing (CS) based algorithm for synthetic
aperture radar (SAR) imaging, aimed at achieving high-resolution imaging. Traditional …

This paper presents a novel Compressive Sensing (CS) algorithm for Synthetic Aperture
Radar (SAR) imaging, designed to overcome the resolution limitations found in conventional …

Compressive sensing (CS) enables imaging with less data, assuming sparsity in certain
domains. We proposed a groundbreaking coarse-to-fine (CTF) estimation method that …

Compressive sensing (CS) theory has achieved significant success in the field of synthetic
aperture radar (SAR) imaging. Recent studies have shown that SAR imaging for sparse …

Along with increasingly intense desire to achieve super high-resolution images, synthetic
aperture radar (SAR) is facing more severe technical challenges such as sampling, storage …

Imaging a target or scene is one of the most important applications of Synthetic Aperture
Radar (SAR). There are many numbers of algorithms to generate SAR images but …

In the area of radar imaging at any frequency band from microwave to optics, the technique
of compressive sensing (CS) enables high resolution with reduced number of antenna …

Synthetic aperture radar (SAR) has extensive applications in both civilian and military fields
for its ability to create high-resolution images of the ground target without being affected by …

Recently, compressive sensing (CS) has been applied in synthetic aperture radar (SAR)
imaging, which is increasingly in the focus of study and shows great potential. In CS-based …

Based on the observation that sparsity assumption is well satisfied in the synthetic aperture
radar (SAR) imaging applications, there is increasing interest in utilizing compressive …