Hyperparameter-free sparse signal direction-of-arrival estimation method with single-snapshot

Based on the sparse representation of the array output model, the issue of direction-of-arrival (DOA) estimation for coherent signals is researched utilizing the single-snapshot data. An interference covariance matrix is defined as a weighed matrix, and the high-precision estimation of single-snapshot DOA is realized by the iterative adaptive solution of a weighted least squares (WLS), abbreviated to WLS-IAE. The computational complexity of the algorithm is analyzed in detail, and compared with that of the classical sparse estimation algorithm. As a sparse representation estimation method, the proposed algorithm not only maintains good estimation performance under non-ideal conditions such as low signal to noise ratio, single snapshot, coherent sources and nearby sources, but also do not require to select hyperparameters, and has low computational complexity and hard real time, which is particularly useful for the real-time measurement and tracking of time-varying DOA with potential practical value. Simulation experiments verify the efficacy of the proposed algorithm. © 2021, Editorial Office of Systems Engineering and Electronics. All right reserved.