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Coprime L-shaped array connected by a triangular spatially-spread electromagnetic-vector-sensor for two-dimensional direction of arrival estimation

机译:通过三角形空间扩展电磁矢量传感器连接的互质L形阵列,用于二维到达方向估计

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摘要

The authors propose a hybrid L-shaped array composed of two sparse scalar arrays and a single triangular spatially-spread electromagnetic-vector-sensor (SS-EMVS) for two-dimensional (2D) direction-of-arrival (DOA) estimation. These two sparse but uniform scalar arrays are placed along the x-axis and y-axis, respectively, which constitute two arms of the L-shaped array. These two arms are connected by an SS-EMVS, which consists of a spatially-spread dipole-triad plus a spatially-spread loop-triad. Further, the inter-dipole/loop spacings of SS-EMVS follow a coprime relationship with the inter-sensor spacings of the L-shaped scalar array. In proposed DOA estimation algorithm, they first perform the vector-cross-product algorithm to SS-EMVS to obtain a high-accuracy but ambiguous direction cosine estimation; they then apply the ESPRIT algorithm to the scalar array on each arm to get another high-accuracy but cyclically ambiguous direction cosine estimation; finally, they adopt the Chinese Remainder Theorem to disambiguate the ambiguous estimations. Because the authors' proposed array has 2D array aperture extension, it can achieve a high angular estimation performance. Moreover, one component of triangular SS-EMVS rather than an SS-EMVS is used as the array unit of two scalar arrays; thus, the whole array cost decreases dramatically. Simulation results validate the array configuration and the developed algorithm.
机译:作者提出了一种混合L形阵列,该阵列由两个稀疏标量阵列和一个三角形空间扩展电磁矢量传感器(SS-EMVS)组成,用于二维(2D)到达方向(DOA)估计。这两个稀疏但均匀的标量阵列分别沿x轴和y轴放置,它们构成L形阵列的两个臂。这两个臂由SS-EMVS连接,该SS-EMVS由空间扩展的偶极三元组和空间扩展的环形三元组组成。此外,SS-EMVS的偶极间/环间距与L形标量阵列的传感器间间距遵循互质关系。在提出的DOA估计算法中,他们首先对SS-EMVS执行向量叉积算法,以获得高精度但模棱两可的方向余弦估计;然后,他们将ESPRIT算法应用于每条臂上的标量阵列,以获得另一种高精度但循环歧义的方向余弦估计;最后,他们采用了中国剩余定理来消除模棱两可的估计。由于作者提出的阵列具有2D阵列孔径扩展,因此可以实现较高的角度估计性能。而且,使用三角形SS-EMVS的一个分量而不是SS-EMVS作为两个标量阵列的阵列单元;因此,整个阵列的成本大大降低。仿真结果验证了阵列配置和开发的算法。

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