基于稀疏谱拟合的超分辨方位估计

Super-resolution DOA estimation based on sparse spectrum fitting

考虑到各阵元接收的实际环境噪声可能是相关的,以及风成噪声和远处航船噪声等因素的影响,环境噪声强度的空间分布可能具有方向性。利用非均匀环境噪声模型,结合稀疏谱拟合算法,提出了一种基于稀疏谱拟合的超分辨方位估计算法。该算法利用空间信号的稀疏性和线性噪声模型拟合误差的l2-范数联合最小化,实现非均匀环境噪声条件下的超分辨方位估计。通过计算机仿真讨论了正则参数和线性噪声模型阶数对算法性能的影响,海上试验结果表明了该算法较传统算法和稀疏谱拟合算法具有更低的旁瓣级和更好的方位分辨能力,同时有效验证了该算法在非均匀环境噪声背景下的超分辨方位估计性能。

The ambient noise at any two different sensors,in practice,may correlate with each other,and the spatial distribution of ambient noise intensity may be directional because of wind and shipping noise sources.A linear harmonic noise model is consid-ered in this paper to appropriately describe the ambient noise.By applying l2-norm penalization of fitting the source covariance model to the estimated spatial covariance and the linear harmonic noise model,super-resolution direction of arrival(DOA)estimation algorithm based on sparse spectrum fitting is proposed.Then,the influence of the regular parameters and the number of linear noise model on the performance of the algorithm is discussed by computer simulations.The performance of the proposed algorithm is verified by the data processing of the sea trial data.