Remote sensing with radar is typically an ill-posed linear inverse problem: a scene is to be
inferred from limited measurements of scattered electric fields. Parsimonious models provide …

Compressive sensing (CS) is a novel sampling paradigm that samples signals in a much
more efficient way than the established Nyquist sampling theorem. CS has recently gained a …

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 …

Radar imaging is a subject of tremendous mathematical richness, with many interesting
applications and many challenging open problems that are of a mathematical nature. Yet the …

This paper presents the first fully polarimetric high-resolution circular synthetic aperture
radar (CSAR) images at L-band (1.3 GHz). The circular data were acquired in 2008 by the …

There is increasing interest in using synthetic aperture radar (SAR) images in automated
target recognition and decision-making tasks. The success of such tasks depends on how …

Signal capture is at the forefront of perceiving and understanding the environment; thus,
imaging plays a pivotal role in mobile vision. Recent unprecedented progress in artificial …

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 …

稀疏微波成像是将稀疏信号处理理论系统性地引入微波成像并有机结合形成的微波成像新理论,
新体制和新方法. 该文阐述了稀疏微波成像中稀疏表征与变换域映射, 稀疏观测约束 …

Sparse signal representations and approximations from overcomplete dictionaries have
become an invaluable tool recently. In this paper, we develop a new, heuristic, graph …