Several problems arising in electromagnetics can be directly formulated or suitably recast for
an effective solution within the compressive sensing (CS) framework. This has motivated a …

Compressive sensing (CS) is currently one the most active research fields in information
engineering and science. The flexibility, robustness, accuracy, effectiveness, and sound …

Compressive sensing (CS) techniques offer a framework for the detection and allocation of
sparse signals with a reduced number of samples. Today, modern radar systems operate …

The problem of imaging arbitrary-shaped targets is addressed through a methodological
generalization of the compressive sensing (CS) paradigm. The Color CS (C-CS) …

The estimation of the directions of arrival (DoAs) of narrow-band signals impinging on a
linear antenna array is addressed within the Bayesian compressive sensing (BCS) …

The application of the compressive sensing (CS) paradigm to retrieve non-single-pixels
contrast profiles is discussed. By exploiting a wavelet representation to model complex …

Learn about the most recent theoretical and practical advances in radar signal processing
using tools and techniques from compressive sensing. Providing a broad perspective that …

Modern radar systems tend to utilize high bandwidth, which requires high sampling rate, and
in many cases, these systems involve phased array configurations with a large number of …

In this paper we give a brief review of compressive sensing (CS) applied to radar. Though
CS theory has been introduced only a few years ago (in 2006, see eg [1]), it today manifests …

Sparsening conformal arrangements is carried out through a versatile Multi-Task Bayesian
Compressive Sensing (MT-BCS) strategy. The problem, formulated in a probabilistic fashion …