基于张量域降噪的宽带DOA估计  

Wideband DOA Estimation Algorithm Based on Tensor Domain Denoising

作　　者：韦娟[1] 郑伟哲 李润宇 WEI Juan;ZHENG Weizhe;LI Runyu(School of Communication Engineering,Xidian University,Xi’an 710071,China)

机构地区：[1]西安电子科技大学通信工程学院,西安710071

出　　处：《北京邮电大学学报》2022年第3期107-111,116,共6页Journal of Beijing University of Posts and Telecommunications

基　　金：国家自然科学基金项目(52075441);陕西省重点研发计划项目(2020ZDLGY06-09)。

摘　　要：针对低信噪比条件下远场宽带信号波达方向(DOA)估计精度低的问题,提出了一种基于张量域降噪的宽带DOA估计算法。首先,联合各子频带数据构造张量信号;然后进行高阶奇异值分解,并利用最小描述长度准则分离信号与噪声;其次,改进协方差矩阵拟合算法,利用L1范数对信号功率进行约束,获得L1约束问题模型并求解;最后,对所有窄带估计结果进行融合得到宽带信号DOA。仿真结果表明,该算法可有效地降噪,同时较求根多重信号分类算法和旋转不变子空间参数估计算法,该算法对DOA估计无需预知信源数目,且在低信噪比条件下具有较小的均方根误差。To tackle the poor accuracy issue in far-filed wideband signal direction of arrival(DOA) estimation under low signal-to-noise ratio conditions, a wideband DOA estimation algorithm is proposed based on tensor domain denoising. First, a tensor is constructed with the data from each sub-band, and then, high-order singular value decomposition is performed on this tensor to separate signals and noise by the minimum description length criterion. Next, the covariance matrix fitting algorithm is improved, and the signal power is constrained by using L1-norm to obtain solving model. Finally, the wideband signal DOA can be obtained by fusing all the narrowband estimation results. Simulation results demonstrate that the proposed algorithm can effectively reduce noise. Compared with root multiple signal classification algorithm and estimation of signal parameters via rotational invariance technique algorithm, the proposed algorithm does not neet to know the number of signals in advance for DOA estimation, and has low root mean square error under low signal-to-noise ratio conditions.

关 键 词：波达方向 低信噪比 高阶奇异值分解 协方差矩阵拟合 

分 类 号：TN912.16[电子电信—通信与信息系统]