Si Weijian, Zhao Pinjiao, Qu Zhiyu
College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China.
Sensors (Basel). 2016 May 31;16(6):789. doi: 10.3390/s16060789.
This paper presents an L-shaped sparsely-distributed vector sensor (SD-VS) array with four different antenna compositions. With the proposed SD-VS array, a novel two-dimensional (2-D) direction of arrival (DOA) and polarization estimation method is proposed to handle the scenario where uncorrelated and coherent sources coexist. The uncorrelated and coherent sources are separated based on the moduli of the eigenvalues. For the uncorrelated sources, coarse estimates are acquired by extracting the DOA information embedded in the steering vectors from estimated array response matrix of the uncorrelated sources, and they serve as coarse references to disambiguate fine estimates with cyclical ambiguity obtained from the spatial phase factors. For the coherent sources, four Hankel matrices are constructed, with which the coherent sources are resolved in a similar way as for the uncorrelated sources. The proposed SD-VS array requires only two collocated antennas for each vector sensor, thus the mutual coupling effects across the collocated antennas are reduced greatly. Moreover, the inter-sensor spacings are allowed beyond a half-wavelength, which results in an extended array aperture. Simulation results demonstrate the effectiveness and favorable performance of the proposed method.
本文提出了一种具有四种不同天线组合的L形稀疏分布矢量传感器（SD-VS）阵列。利用所提出的SD-VS阵列，提出了一种新颖的二维（2-D）到达方向（DOA）和极化估计方法，以处理不相关源和相干源共存的场景。基于特征值的模对不相关源和相干源进行分离。对于不相关源，通过从估计的不相关源阵列响应矩阵中提取嵌入在导向矢量中的DOA信息来获得粗略估计，这些粗略估计用作粗参考，以消除从空间相位因子获得的具有循环模糊性的精细估计。对于相干源，构造四个汉克尔矩阵，以与不相关源类似的方式分辨相干源。所提出的SD-VS阵列每个矢量传感器仅需要两个并置天线，因此大大降低了并置天线之间的互耦效应。此外，传感器间间距允许超过半波长，这导致阵列孔径扩展。仿真结果证明了所提方法的有效性和良好性能。
