Dual-Polarized RIS Assisted Super-Resolution DOA Estimation for UAV Communications

In recent years, intelligent reflecting surfaces (RIS) have emerged as a key technology in the field of wireless communications. To address the limitations of traditional singlepolarized RIS in terms of degree-of-freedom utilization, in this paper we put forward a dual-polarized RIS-assisted unmanned aerial vehicle (UAV) multi-parameter direction-of-arrival (DOA) joint estimation method. A joint reflection matrix for the dualpolarized RIS is designed, enabling the resolution of more signal sources under the same physical aperture. In terms of algorithm design, the random optimization subspace mapping (ROSM) method is employed for RIS phase optimization, which ensures algorithm convergence while effectively reducing computational complexity. Finally, the Multiple Signal Classification (MUSIC) algorithm is employed to perform a global peak search on the spatial spectrum function. By computing the candidate solutions for DOA corresponding to the extremal points of the spectrum function and combining with the orthogonality principle of the signal subspace, high-precision estimation of the incident signal's DOA is achieved. Simulation results demonstrate that, compared to existing methods and traditional single-polarized RIS schemes, the proposed method enhances estimation accuracy and exhibits superior performance advantages.