In this letter, a novel relocating enhanced nested array (RENA) configuration is proposed. Compared with most existing sparse array configurations, the proposed RENA has a hole-free difference co-array, simple closed expressions for the array geometry and degrees of freedom (DOFs), and also achieves more consecutive DOFs. Based on the above good properties of the proposed RENA, we improve a root multi-signal classification algorithm based on pseudo-noise subspace (PNS-root-MUSIC) for direction of arrival (DOA) estimation. The PNS-root-MUSIC algorithm has lower algorithm complexity due to no exhaustive spectral peak search, and takes full advantage of the larger hole-free co-array of the proposed RENA, yielding a higher accuracy of DOA estimation. The results of theoretical analysis and simulations demonstrate the superior performance of the proposed RENA. The simulation results show that the improved PNS-root-MUSIC algorithm has better DOA estimation performance compared with that of existing algorithms.

中文翻译：

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基于伪噪声子空间的增强型嵌套阵列重定位DOA估计

在这封信中，提出了一种新的重定位增强嵌套阵列 (RENA) 配置。与大多数现有的稀疏阵列配置相比，所提出的 RENA 具有无孔差分共阵列、阵列几何和自由度 (DOF) 的简单封闭表达式，并且还实现了更多的连续自由度。基于所提出的 RENA 的上述良好特性，我们改进了一种基于伪噪声子空间 (PNS-root-MUSIC) 的根多信号分类算法，用于波达方向 (DOA) 估计。PNS-root-MUSIC算法由于没有穷举谱峰搜索，算法复杂度较低，并充分利用了所提出的RENA较大的无孔共阵列，产生了更高的DOA估计精度。理论分析和模拟结果证明了所提出的 RENA 的优越性能。仿真结果表明改进的PNS-root-MUSIC算法与现有算法相比具有更好的DOA估计性能。