Coded Aperture Radar Imaging Using Reconfigurable Intelligent Surfaces

TL;DR

This paper introduces a novel radar imaging method that employs reconfigurable intelligent surfaces and compressive sensing to achieve high-quality scene recovery with a single transceiver, optimizing phase shifts for better imaging.

Contribution

It presents a new approach combining RIS and compressive sensing for radar imaging, including a gradient descent algorithm for phase shift design, enabling effective scene reconstruction.

Findings

Successful recovery of point scatterers and extended targets in simulations

Proposed RIS phase shift design improves observation coherence

Method reduces hardware complexity by using a single transceiver

Abstract

In this paper, we focus on radar imaging using active sensing with a single transceiver and reconfigurable intelligent surface (RIS). RISs are arrays with tunable passive phase shifter elements that can modify the propagation channel. The RIS reflects each transmit pulse with a different phase profile. We use compressive sensing to recover the radar scene from observations at the single-antenna receiver. We also provide a projected gradient descent algorithm to design the RIS phase shifts to obtain minimally coherent observations required for recovery. Through numerical simulations, we demonstrate that the proposed method recovers radar scenes with point scatterers and extended targets.