A Compressive Sensing-Based Approach for Millimeter-Wave Imaging Compatible with Fourier-Based Image Reconstruction Techniques

The unique characteristics of the millimeter-wave (mmW) frequency band have led to its widespread use in various fields such as communications, imaging, and wireless sensing. This paper addresses two different mmW imaging structures, monostatic and multistatic, in the face of a sparse spatial sampling scenario. By using compressive sensing theory, a solution for image reconstruction, consistent with fast Fourierbased techniques, is presented with compressed data obtained from monostatic imaging. This solution is then generalized to a multiple-input multiple-output (MIMO) imaging case using a multistatic-to-monostatic conversion. Reconstructed images from numerical and experimental data show the satisfactory performance of the presented approach.