Direction Finding Method for Wideband Signals Based on Sparse Bayesian Learning with Non-Uniform Metasurfaces

This paper proposes a wideband signal direction finding method based on Sparse Bayesian Learning (SBL) with a non-uniform array arrangement of metasurfaces. The Space-Time-Coding Metasurface (STMC) enables single-channel Direction of Arrival (DOA) estimation, offering significant advantages over phased array antennas in terms of cost and energy consumption. However, the uniform arrangement of traditional metasurface units may result in the inability to install two units within a half-wavelength range at the operating frequency. To address this issue, this study adopts a non-uniform design approach for the STMC unit array and integrates the SBL method for DOA estimation of Linear Frequency Modulation (LFM) signals, thereby reducing system complexity and hardware costs while improving convergence speed, direction finding accuracy, and anti-interference capability. Simulation experiments demonstrate that the proposed method achieves higher estimation accuracy and convergence efficiency compared to other algorithms, while also exhibiting stronger robustness.