Two-Bit RIS-Aided NLOS DOA Based on Fast Zoomed SBL

Direction of arrival (DOA) estimation of non-line-of-sight (NLOS) links assisted by reconfigurable intelligent surface (RIS) is a critical technology in the wireless communication field. The phase control precision and implementation complexity of RIS systems exhibit direct dependence on the quantization bit depth employed in their configuration. Furthermore, the estimation accuracy of the RIS aided DOA estimation methodology under the SBL framework experiences substantial degradation when grid mismatch conditions occur. In this article, we design a two-bit RIS aided system, and propose a DOA estimation method based on fast zoomed sparse Bayesian learning (SBL). Firstly, under the minimum weighted integral sidelobe level (WISL) criterion, a coding scheme of two-bit orthogonal phase matrix is proposed to realize low cost and accurate phase control by using four adjustable phases. Secondly, we construct an observation model composed of Fourier matrices, and then propose a zoomed dictionary based SBL algorithm. This approach yields more accurate angular information. Additionally, a circulant-skew circulant Gohberg-Semencul (CSCGS) decomposition algorithm is proposed to calculate the inversion of covariance matrix in the iterative process of SBL, which can significantly reduce the computational complexity. Simulation results demonstrate the feasibility of the proposed method under any number of snapshots and its superior performance compared to existing methods.