High-precision Broadband DOA Estimation Method Based on Sparse Reconstruction

Direction of Arrival (DOA) estimation is a key technique in the field of array signal processing and has significant applications in radar detection, wireless communication, and sonar perception. Traditional DOA estimation methods include parametric model-based, spatial filtering, and subspace-based approaches, each achieving high-precision DOA estimation through different means. This paper addresses the issue of DOA estimation for broadband signals by proposing a high-precision estimation method based on sparse reconstruction. The method constructs a reception model for broadband signals in an array system, exploits the sparsity characteristics of the signals in the spatial domain, and formulates the DOA estimation problem as a sparse optimization problem. Different dictionary matrices are constructed for signals at various frequencies, and an iterative algorithm is employed to solve the problem, achieving DOA estimation for broadband signals. Simulation results demonstrate that the proposed method outperforms existing algorithms under various signal-to-noise ratios, numbers of antennas, signal bandwidths, and snapshot counts, showing particularly prominent broadband characteristics.