Joint Angle and Rang Estimation with Low-Cost Ris-Assisted FDA Direction Finding System

This article explores the integration of Reconfigurable Intelligent Surfaces (RIS) with Frequency Diversity Array (FDA) radars to advance sixth-generation (6G) communication technologies. The study specifically addresses the challenge of low-cost RIS-assisted FDA radar localization. To solve the joint angle-range estimation problem, we employ the Atomic Norm Minimization (ANM) approach. Traditional semidefinite programming (SDP) methods, often used for this purpose, suffer from high complexity and dependence on interior point methods. To improve efficiency, we propose an iterative solution based on the Alternating Direction Method of Multipliers (ADMM). Our simulation results demonstrate that this ADMM-based method not only enhances parameter estimation accuracy but also maintains low computational complexity, outperforming existing algorithms. This research marks a significant step forward in radar localization technology, effectively combining RIS with FDA radars and introducing a novel, efficient method for precise signal processing.