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Robust adaptive beamforming in the presence of strong desired signal and DOA mismatch

机译:在强烈的期望信号和DOA不匹配的情况下进行稳健的自适应波束成形

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The performances of most previous beamformers degrade dramatically when the desired signal (DS) of high signal-to-noise ratio (SNR) is present in the training data with direction-of-arrival (DOA) mismatch. In this paper, two new robust adaptive beamformers are presented to achieve robustness over a large range of SNR. The basic ideas of the presented beamformers are based on the interference-plus-noise covariance matrix reconstruction and two different steering vector estimation methods. Compared with the previous steering vector estimation method, they have good performance while have less computational complexity and don't need any specific optimization software. Simulation results demonstrate that the performances of the proposed beamformers are close to the optimal values over a large range of SNR.
机译:当在到达方向(DOA)不匹配的训练数据中存在高信噪比(SNR)的所需信号(DS)时,大多数以前的波束成形器的性能都会大大降低。在本文中,提出了两种新型的鲁棒自适应波束形成器,以在较大的SNR范围内实现鲁棒性。提出的波束形成器的基本思想是基于干扰加噪声协方差矩阵重构和两种不同的转向矢量估计方法。与以前的转向矢量估计方法相比,它们具有良好的性能,同时具有较低的计算复杂度,并且不需要任何特定的优化软件。仿真结果表明,所提出的波束形成器的性能在较大的SNR范围内接近最佳值。

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