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L-shaped coprime array structures for DOA estimation

机译:用于DOA估计的L形共阵列结构

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摘要

This paper proposes a new sparse array geometry for 2-D (azimuth and elevation) directionof-arrival (DOA) estimation based on coprime sampling. The proposed array structure is L-shaped coprime array (LCA) whose each portion is one dimensional coprime linear arrays in y- and z-dimensions. Each portion of the array is used separately for 1-D azimuth and elevation angle estimation. In order to obtain the paired DOA estimates the cross-covariance matrix of two portion of the array is utilized and the paired DOA angles are estimated. LCA provides to estimate K <= MN source directions with 2M+ N-1 sensors in each portion and totally 4M + 2N - 3 sensor elements. The proposed method is evaluated through numerical simulations and its performance is compared with other coprime planar array structures. It is shown that LCA has less computational complexity together with less real sensor elements and it provides superior performance as compared to the conventional 2-D coprime planar arrays.
机译:本文提出了一种基于CopRime采样的2-D(方位角和高度)方向 - 到达(DOA)估计的新稀疏阵列几何形状。 所提出的阵列结构是L形的基准阵列(LCA),其每个部分是Y和Z尺寸中的一维基准线阵列。 阵列的每个部分分别用于1-D方位角和仰角估计。 为了获得成对的DOA估计,利用两部分阵列的交叉协方差矩阵,并且估计成对的DOA角度。 LCA提供了在每个部分中的2M + N-1传感器和完全4M + 2N - 3传感器元件的估计k <= Mn源方向。 通过数值模拟评估所提出的方法,并将其性能与其他CopRime平面阵列结构进行比较。 结果表明,与传统的2-D共协调平面阵列相比,LCA具有较少的计算复杂性,与实际传感器元件较少,并且提供卓越的性能。

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