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DOA estimation via ULA with mutual coupling in the presence of non-uniform noise

机译:在存在非均匀噪声的情况下,通过ULA估计通过ULA估计

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摘要

It is well known that classic direction-of-arrival (DOA) estimation methods yield poor accuracy and low resolution in the presence of mutual coupling and non-uniform noise. To tackle this problem, a DOA estimation method for jointly optimizing noise-free covariance matrix and mutual coupling coefficient is proposed in this paper. Based on the least squares (LS) criterion, the signal subspace and noise-free covariance matrix under mutual coupling can be obtained in an iterative manner. With the determined signal/noise subspace, the mutual coupling matrix can be reconstructed and the covariance one is estimated after mutual coupling compensation. Finally, the noise-free covariance matrix is preprocessed by spatial smoothing strategy and then used to determine the DOAs with the help of traditional DOA estimators. Compared to the conventional DOA estimation methods, simulation results demonstrate that, the proposed method can suppress the non-uniform noise significantly, alleviate the effect of mutual coupling on spatial smoothing technique obviously, as well as improve the DOA estimation performance in the case of coherent signals considerably. (C) 2019 Elsevier Inc. All rights reserved.
机译:众所周知,经典的到达(DOA)估计方法在存在相互耦合和非均匀噪声时产生差的准确度和低分辨率。为了解决这个问题,本文提出了一种用于共同优化无噪声协方差矩阵和相互耦合系数的DOA估计方法。基于最小二乘(LS)标准,可以以迭代方式获得相互耦合下的信号子空间和无噪声协方差矩阵。利用所确定的信号/噪声子空间,可以重建互联耦合矩阵,并且在相互耦合补偿之后估计协方差。最后,通过空间平滑策略预处理无噪声协方差矩阵,然后用于在传统的DOA估计器的帮助下确定DOA。与传统的DOA估计方法相比,仿真结果表明,所提出的方法可以显着抑制非均匀噪声,缓解相互耦合对空间平滑技术的影响显然,以及改善了在连贯的情况下的DOA估计性能信号很大。 (c)2019 Elsevier Inc.保留所有权利。

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