基于子空间干扰功率估计的多素数阵列鲁棒自适应波束形成

Sicong Sun, Z. Ye, Xingyu Zhu
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引用次数: 0

摘要

与均匀线性阵列(ULA)相比,在相同物理传感器数量的情况下,共质阵列可以获得更大的阵列孔径,从而提高了空间分辨率,减小了相互耦合的影响。同时,通过重构虚拟阵列域的采样协方差矩阵来提高系统的自由度。本文提出了一种基于协素数阵列的鲁棒自适应波束形成算法。在虚拟阵列域提出了一种新的基于子空间的方法来估计干扰的功率和到达方向,并获得了到达方向增强的能力。仿真结果证明了该方法的鲁棒性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robust Adaptive Beamforming for Coprime Array Based on Interference Power Estimation via Subspace
Compared with uniform linear array (ULA), the coprime array can obtain larger array aperture with the same number of physical sensors, which leads to higher spatial resolution and less effect of mutual coupling. Also, the degrees of freedom (DOFs) can be increased by reconstructing the sampling covariance matrix (SCM) in virtual array domain. In this paper, we propose a robust adaptive beamforming (RAB) algorithm based on coprime array. A novel subspace based method is performed in virtual array domain to estimate the power and direction of arrival (DOA) of interference, which also obtains the ability for DOFs enhancement. Simulation results demonstrate the robustness and effectiveness of the proposed method.
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