Radar Cross Section Characterization of Quantized Reconfigurable Intelligent Surfaces

TL;DR

This paper introduces a low-complexity, quantized RIS radar framework with closed-form RCS expressions, validated through simulations and experiments, enhancing detection in shadowed regions.

Contribution

It develops analytical RCS models for quantized RIS, validated by measurements, enabling programmable electromagnetic wavefront manipulation for improved radar detection.

Findings

Analytical RCS expressions match electromagnetic simulations.

Experimental RIS demonstrates beam steering and detection of micro-Doppler signatures.

Quantized RIS effectively enhances radar detection in challenging scenarios.

Abstract

We present a radar sensing framework based on a low-complexity, quantized reconfigurable intelligent surface (RIS) that enables programmable manipulation of electromagnetic wavefronts for enhanced detection in non-specular and shadowed regions. We develop closed-form expressions for the scattered field and radar cross section (RCS) of phase-quantized RIS apertures based on aperture field theory, accurately capturing the effects of quantized phase, periodicity, and grating lobes on radar detection performance. The theory enables us to analyze the RIS's RCS along both the forward and backward paths from the radar to the target. The theory is benchmarked against full-wave electromagnetic simulations incorporating realistic unit-cell amplitude and phase responses. To validate practical feasibility, a $[16\times10]$ 1-bit RIS operating at 5.5 GHz is fabricated and experimentally characterized inside an anechoic chamber. Measurements of steering angles, beam-squint errors, and peak-to-specular ratios of the RCS patterns exhibit strong agreement with analytical and simulated results. Further experiments demonstrate that the RIS can redirect the beam in a non-specular direction and recover micro-Doppler signatures that remain undetectable with a conventional radar deployment.