Compressive sensing as applied to electromagnetics: advances, comparisons, and applications

Some of the most recent advances in the application of Compressive Sensing (CS) strategies to Electromagnetics are reviewed and suitable applicative examples are provided. Towards this end, the formulation of classical CS problems is first reviewed, and the exploitation of Bayesian strategies is considered towards this end. The motivation, advantages, and drawbacks of BCS algorithms as applied to sparse array synthesis, antenna diagnosis, and inverse scattering problems are discussed. A set of numerical examples are reported to assess the features and potentialities of CS within each applicative framework.