Radar Cross Section Characterization of Quantized Reconfigurable Intelligent Surfaces
This work addresses radar sensing limitations in challenging environments for applications like surveillance or autonomous systems, representing an incremental advancement with specific experimental validation.
The paper tackled the problem of enhancing radar detection in non-specular and shadowed regions by developing a framework using a quantized reconfigurable intelligent surface (RIS), resulting in closed-form expressions for radar cross section validated through simulations and experiments with a fabricated RIS that demonstrated beam redirection and recovery of undetectable micro-Doppler signatures.
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.