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首页> 外文期刊>AEU: Archiv fur Elektronik und Ubertragungstechnik: Electronic and Communication >A covariance matrix shrinkage method with Toeplitz rectified target for DOA estimation under the uniform linear array
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A covariance matrix shrinkage method with Toeplitz rectified target for DOA estimation under the uniform linear array

机译:均匀线性阵列下的DOA估计TOEPLITZ校正目标的协方差矩阵收缩方法

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AbstractA covariance matrix shrinkage method is proposed to make an improvement of the direction of arrival (DOA) estimation under a uniform linear array in a scenario where the number of sensors is large and the sample size is relatively small. The main contribution is that we provide a shrinkage target with Toeplitz structure and deduce a closed-form estimation of the shrinkage coefficient. The closed-form and the expectation of the shrinkage coefficient estimate are calculated based on the unbiased and consistent estimates of the trace and moments of a Wishart distributed covariance matrix. The statistical property of the shrinkage coefficient estimate is discussed through theoretical analysis and simulations, which demonstrate the shrinkage coefficient estimate can ensure that the proposed covariance matrix estimate is a good compromise between the sample covariance matrix (SCM) and the target. The root-mean-square-error (RMSE) simulations of DOA estimation show that the proposed method can improve the multiple signal classification (MUSIC) DOA estimation performance in the case of low signal-to-noise ratio (SNR) with small sample size, and also can provide a satisfactory performance at high SNR.]]>
机译:<![cdata [ 抽象 提出了一种协方差矩阵收缩方法,以提高均匀的到达方向(DOA)估计线性阵列在场景中,传感器的数量大并且样本大小相对较小。主要贡献是,我们提供了具有Toeplitz结构的收缩靶标,并推导出收缩系数的闭合估计。基于Wishart分布式协方差矩阵的迹线和时刻的无偏见和一致估计来计算闭合形式和收缩系数估计的期望。通过理论分析和模拟讨论了收缩系数估计的统计性质,其证明了收缩系数估计可以确保所提出的协方差矩阵估计是样本协方差矩阵(SCM)和目标之间的良好折衷。 DOA估计的根均方误差(RMSE)模拟表明,该方法可以在具有小样本大小的低信噪比(SNR)的情况下改善多个信号分类(音乐)DOA估计性能,并且还可以在高SNR提供令人满意的性能。 ]]>

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