In this paper, a sparse nonuniform rectangular array based on spatially spread electromagnetic vector sensor (SNRA-SSEMVS) is introduced, and a method for estimating 2D-direction of arrival (DOA) and polarization is devised. Firstly, according to the special structure of the sparse nonuniform rectangular array (SNRA), a set of accurate but ambiguous direction-cosine estimates can be obtained. Then the steering vector of spatially spread electromagnetic vector sensor (SSEMVS) can be extracted from the array manifold to obtain the coarse but unambiguous direction-cosine estimates. Finally, the disambiguation approach can be used to get the final accurate estimates of 2D-DOA and polarization. Compared with some existing methods, the SNRA configuration extends the spatial aperture and refines the parameters estimation accuracy without adding any redundant antennas, as well as reduces the mutual coupling effect. Moreover, the proposed algorithm resolves multiple sources without the priori knowledge of signal information, suffers no ambiguity in the estimation of the Poynting vector, and pairs the x-axis direction cosine with the y-axis direction cosine automatically. Simulation results are given to verify the effectiveness and superiority of the proposed algorithm.

中文翻译：

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由空间扩展电磁矢量传感器组成的稀疏非均匀矩形阵列的联合2D-DOA和极化估计

本文介绍了一种基于空间扩展电磁矢量传感器（SNRA-SSEMVS）的稀疏非均匀矩形阵列，并提出了一种估计二维到达方向（DOA）和极化的方法。首先，根据稀疏非均匀矩形阵列（SNRA）的特殊结构，可以获得一组准确但不明确的方向余弦估计。然后，可以从阵列歧管中提取空间扩展电磁矢量传感器（SSEMVS）的转向矢量，以获得粗略但明确的方向余弦估计。最后，消歧方法可用于获得2D-DOA和极化的最终准确估计。与一些现有方法相比，SNRA配置扩大了空间孔径，并在不增加任何冗余天线的情况下改善了参数估计的准确性，并降低了相互耦合效应。此外，所提出的算法在没有先验信号信息知识的情况下解析了多个源，在Poynting矢量的估计中没有歧义，并且自动将x轴方向余弦与y轴方向余弦配对。仿真结果验证了所提算法的有效性和优越性。并自动将x轴方向的余弦与y轴方向的余弦配对。仿真结果验证了所提算法的有效性和优越性。并自动将x轴方向的余弦与y轴方向的余弦配对。仿真结果验证了所提算法的有效性和优越性。