Park Yongsung, Gerstoft Peter
Scripps Institution of Oceanography, University of California San Diego, La Jolla, California 92093-0238, USA.
J Acoust Soc Am. 2022 Jun;151(6):3828. doi: 10.1121/10.0011617.
This paper presents gridless sparse processing for direction-of-arrival (DOA) estimation. The method solves a gridless version of sparse covariance-based estimation using alternating projections. Gridless sparse DOA estimation is represented by the reconstruction of Toeplitz-structured low-rank matrices, which our method recovers by alternatively projecting a solution matrix. Compared to the existing gridless sparse methods, our method improves speed and accuracy and considers non-uniformly configured linear arrays. High-resolution and reliable DOA estimation are achieved even with single-snapshot data, coherent sources, and non-uniform arrays. Simulation results demonstrate performance improvements compared to the existing DOA estimators, including gridless sparse methods. The method is illustrated using experimental data from a real ocean experiment.
本文提出了用于波达方向（DOA）估计的无网格稀疏处理方法。该方法使用交替投影解决了基于稀疏协方差估计的无网格版本问题。无网格稀疏DOA估计通过Toeplitz结构低秩矩阵的重构来表示，我们的方法通过交替投影一个解矩阵来恢复该矩阵。与现有的无网格稀疏方法相比，我们的方法提高了速度和精度，并考虑了非均匀配置的线性阵列。即使使用单快照数据、相干源和非均匀阵列，也能实现高分辨率和可靠的DOA估计。仿真结果表明，与现有的DOA估计器（包括无网格稀疏方法）相比，性能有所提高。使用来自真实海洋实验的实验数据对该方法进行了说明。
