基于可重构反射器的定位：方案与性能分析
Positioning with Flexible Reflectors: Solution and Performance Analysis
AI总结：
本文针对视距不可用场景，提出可重构反射器集群辅助的目标定位方案，推导克拉美罗下界优化反射器参数，仿真显示方案性能接近理论极限，为相关部署提供指导。
AI中文摘要：
可重构反射器（FRs）已成为一种低成本、高能效的解决方案，可在各类应用中重塑电磁传播环境。本文研究了视距（LoS）路径不可用场景下，由FR集群辅助的目标定位问题。利用FR产生的虚拟视距路径，提出了一种简单却精准的严重遮挡条件下的定位估计器。为表征该方案的性能极限，推导了克拉美罗下界（CRLB），并以此优化FR的位置与朝向。此外，考虑FR的随机部署，表征了CRLB分布，揭示了不同网络配置对定位精度的影响。仿真结果表明，所提方案的性能接近CRLB，推导的分析结果为FR部署与网络设计提供了实用指导。
英文摘要：
Flexible reflectors (FRs) have emerged as a low-cost and energy-efficient solution for reshaping electromagnetic propagation environments across a wide range of applications. This paper investigates FR-swarm-assisted target localization in scenarios where line-of-sight (LoS) paths are unavailable. By leveraging the virtual LoS paths created by the FRs, a simple yet accurate estimator is proposed for localization under severe blockage conditions. To characterize the performance limits of the proposed scheme, we derive the Cramer-Rao lower bound (CRLB) and use it to optimize the positions and orientations of the FRs. Furthermore, by accounting for random FR deployment, we characterize the CRLB distribution and reveal how different network configurations affect localization accuracy. Simulation results demonstrate that the developed scheme closely approaches the CRLB performance, while the derived analytical results provide useful guidelines for FR deployment and network design.
