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 …

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

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

Compressive Sensing (CS) theory has been used for Synthetic Aperture Radar (SAR)
imaging due to the sparsity feature of SAR images. Therefore, some well-known CS …

We propose an algorithm for synthetic aperture radar (SAR) imaging of dominant scatterers
based on the theory of Compressive Sensing (CS). The SAR raw data is randomly sampled …

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 …

Synthetic aperture radar system has an ability to generate high resolution image data. It
requires high rate data acquisition, huge data storage, high power consumption and high …

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 …

Traditional synthetic aperture radar (SAR) utilizes Shannon-Nyquist theorem for high
bandwidth signal sampling, which induces the complicated system, and it is difficult to …

Synthetic aperture radar (SAR) is a remote sensing system producing images with high
resolution. It is not influenced by time and weather. As the increase of resolution and …