Reconfigurable Intelligent Surface Aided Sparse DOA Estimation Method With Non-ULA

Abstract

The direction of arrival (DOA) estimation problem is addressed in this letter. A reconfigurable intelligent surface (RIS) aided system for the DOA estimation is proposed. Unlike traditional DOA estimation systems, a low-cost system with only one complete functional receiver is given by changing the phases of the reflected signals at the RIS elements to realize the multiple measurements. Moreover, an atomic norm-based method is proposed for the DOA estimation by exploiting the target sparsity in the spatial domain and solved by a semi-definite programming (SDP) method. Furthermore, the RIS elements can be any geometry array for practical consideration, so a transformation matrix is formulated and different from the conventional SDP method. Simulation results show that the proposed method can estimate the DOA more accurately than the existing methods in the non-uniform linear RIS array.

References in corpus (5)

• Super-Resolution Delay-Doppler Estimation for OFDM Passive Radar
• Harnessing Sparsity over the Continuum: Atomic Norm Minimization for Super Resolution
• TRICE: A Channel Estimation Framework for RIS-Aided Millimeter-Wave MIMO Systems
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Cited by in corpus (4)

• Low-Cost Beamforming and DOA Estimation Based on One-Bit Reconfigurable Intelligent Surface
• DNN-DANM: A High-Accuracy Two-Dimensional DOA Estimation Method Using Practical RIS
• NoncovANM: Gridless DOA Estimation for LPDF System
• R-SFLLM: Jamming Resilient Framework for Split Federated Learning with Large Language Models