Electromagnetic imaging using compressive sensing

We develop a near-field compressive sensing (CS) estimation scheme for localizing scattering objects in vacuum. The potential of CS for localizing sparse targets was demonstrated in previous work. We extend the standard far-field approach to near-field scenarios by employing the electric field integral equation to capture the mutual interference among targets. We show that the advanced modeling improves the capability to resolve closely spaced targets. We compare the performance of our algorithm with the performances of CS applied to point targets and beamforming. In this paper, we consider two-dimensional (2D) scatterers. However, the results and conclusions can be extended to three-dimensional (3D) problems.