RIS-enabled computational radar coincidence imaging

We present an imaging technique using reconfigurable intelligent surfaces (RISs) that combines radar coincidence imaging and compressive imaging. In this framework, RISs are divided into subpanels to redirect beams toward a region of interest (ROI), where their interference creates confined and spatially diverse patterns. These patterns enable interrogation of the ROI using a few measurements, which can be processed computationally to produce high-quality images. Compared to raster scanning, this method requires fewer measurements and, unlike random-pattern techniques, offers a higher signal-to-noise ratio and robustness to clutter. Numerical simulations confirm the proposed method's efficacy and contrast it against other approaches.