Positioning with Flexible Reflectors: Solution and Performance Analysis

2026-08-14

AI Summary

This study addresses the challenge of target localization in non-line-of-sight (NLOS) environments by proposing a virtual line-of-sight solution utilizing clusters of flexible reflectors. A high-precision localization estimator is designed, and the Cramér-Rao Lower Bound (CRLB) is derived to establish an optimal reflector deployment strategy. Simulation results demonstrate that the proposed scheme achieves localization accuracy approaching the theoretical limit while revealing the critical impact of network topology configuration on system performance. Consequently, this work provides effective theoretical support and practical guidance for high-precision localization in NLOS scenarios and the design of reflector-assisted networks.

Abstract

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.

Problem

• Target Localization
• Flexible Reflectors
• Non-Line-of-Sight
• Cramer-Rao Lower Bound
• Performance Analysis

Innovation

• Flexible Reflectors
• Target Localization
• Cramer-Rao Lower Bound
• Virtual LoS
• Swarm Deployment