AI 中文总结
本文提出V-RIS框架，仅用四个角子阵列和单天线接收机，基于稀疏RIS实现虚拟孔径DoA估计，精度接近全孔径基准，室外原型仅用25%可编程单元即可将角误差控制在1°内。
AI 中文摘要
大孔径可重构智能表面（RIS）可实现高分辨率二维到达方向（DoA）估计，但现有方法仍将硬件成本与控制开销和孔径大小绑定。为解耦有效感知孔径与物理部署的RIS单元数量，本文提出V-RIS，一种用于虚拟孔径表面场重建与DoA估计的框架。V-RIS仅使用四个角子阵列和单天线接收机，通过在多个RIS相位配置下收集的接收机观测值重建虚拟孔径表面场，再对重建的虚拟孔径表面场执行DoA估计。本文关键发现是，远场照射下，离散RIS表面场沿两个孔径轴均满足有限阶空间递推关系。我们通过RIS编码的接收机观测值实现数据级一致性，通过远场空间递推关系实现传播一致性，同时采用保留连续局部单元与长孔径基线的四角部署几何结构。为提升实际接收机观测的鲁棒性，我们采用偏差不变的接收机域损失，以抑制准静态硬件失真与配置不变的多径分量。大量仿真表明，V-RIS的DoA精度接近全孔径基准，且生成的频谱比矩阵补全与最小二乘基准更清晰；室外原型进一步验证了该设计：仅使用25%的可编程单元，V-RIS可将俯仰角与方位角误差均保持在真实值的1°以内。
英文摘要
Large-aperture reconfigurable intelligent surfaces (RISs) enable high-resolution 2D direction-of-arrival (DoA) estimation, but existing approaches still tie hardware cost and control overhead to aperture size. To decouple the effective sensing aperture from the number of physically deployed RIS elements, we present V-RIS, a framework for virtual-aperture surface-field reconstruction and DoA estimation. V-RIS uses only four corner subarrays and a single-antenna receiver to reconstruct the virtual-aperture surface field from receiver observations collected under multiple RIS phase configurations, and then performs DoA estimation on the reconstructed virtual-aperture surface field. Our key observation is that, under far-field illumination, the discretized RIS surface field satisfies finite-order spatial recurrences along both aperture axes. We enforce data-level consistency through the RIS-coded receiver observations and propagation consistency through the far-field spatial recurrence, while using a four-corner deployment geometry that retains both contiguous local elements and long aperture baselines. To improve robustness in practical receiver observations, we adopt a bias-invariant receiver-domain loss that suppresses quasi-static hardware distortions and configuration-invariant multipath contributions. Extensive simulations show that V-RIS approaches the DoA accuracy of a full-aperture benchmark while producing cleaner spectra than matrix-completion and least-squares baselines. An outdoor prototype further validates the design: with only 25\% programmable elements, V-RIS keeps both elevation and azimuth errors within $1^\circ$ of the ground truth.
