Real-Valued DOA Estimation Utilizing Enhanced Covariance Matrix With Unknown Mutual Coupling
Real-Valued DOA Estimation Utilizing Enhanced Covariance Matrix With Unknown Mutual Coupling
复制标题
利用具有未知互耦的增强协方差矩阵进行实值 DOA 估计
DOI：
10.1109/lcomm.2022.3148260
复制
发表时间：
2022-04-01
期刊：
影响因子：
--
通讯作者：
Jin, Ming
中科院分区：
文献类型：
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作者：
Tian, Ye;Wang, Ran;Jin, Ming
大规模多输入多输出（MIMO）系统中，由于空间的限制，阵列往往会受到未知互耦的影响。与此同时，少量的数据观测记录可能共存。这两个限制带来了准确的波达方向（DOA）估计的挑战。为了克服这一挑战，本文提出了一种实值DOA估计方法，其核心是通过内在机理消除未知互耦的影响，并在小样本情况下，利用线性收缩技术结合Rao-Blackwell Ledoit-Wolf（RBLW）估计器提高采样协方差阵的估计精度。考虑到直接使用RBLW估计器的收缩目标可以在低信噪比下得到改进的DOA估计，本文还提出了一种基于特征值比较的改进方法。仿真结果表明，该方法可以提供一个更高的精度，降低了复杂度。
Due to the space limitations, the array in a massive multiple-input multiple-output (MIMO) system often suffers from unknown mutual coupling. Meanwhile, small records of data observations may coexist. Such two limitations bring a challenge for accurate direction-of-arrival (DOA) estimation. To conquer this challenge, a real-valued DOA estimation method is proposed in this letter, whose core is to eliminate the influence of unknown mutual coupling by the inherent mechanism, as well as enhance the sampled covariance matrix estimation with the linear shrinkage technique combined with Rao-Blackwell Ledoit-Wolf (RBLW) estimator under the case of small sample size. Considering the result that the direct usage of the shrinkage target of RBLW estimator can yield an improved DOA estimation under low SNRs, a modified method depends on the eigenvalue comparison is also addressed. Simulation results show that the proposed method can provided an increased accuracy with reduced complexity.