This article presents a survey of recent research on sparsity-driven synthetic aperture radar
(SAR) imaging. In particular, it reviews 1) the analysis and synthesis-based sparse signal …

In this paper, we present a solution to the complex synthetic aperture radar (SAR) imaging
problem within a constrained optimization formulation where the objective function includes …

In this paper, we introduce a synthetic aperture radar (SAR)-based millimeter-wave imaging
system for highresolution imaging of human skin, in addition to traditional nondestructive …

Imaging via synthetic aperture radar (SAR) is a well-established technique for effective
scene reconstruction, with resolution up to a few centimeters. The measurement process …

In this paper, SAR image reconstruction with joint phase error estimation (autofocusing) is
formulated as an inverse problem. An optimization model utilising a sparsity-enforcing …

Inverse problems model real world phenomena from data, where the data are often noisy
and models contain errors. This leads to instabilities, multiple solution vectors and thus ill …

Direct image formation in synthetic aperture radar (SAR) involves processing of data
modeled as Fourier coefficients along a polar grid. Often in such data acquisition processes …

Synthetic aperture radar (SAR) systems produce high resolution, two dimensional imaging
of areas of environmental interest. SAR interferometry and tomography enables these …

Linearly constrained dictionary learning (LCDL). The dictionary learning problem and the K-
SVD algorithm can be modified to a model including an unknown multiplicative distortion to …

Interaction of Reflectors in a Range Cell▶ Random interference: Speckle dominates images
due to many random reflectors in a range cell inducing multiplicative noise in the …