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Robust adaptive beamforming based on interference covariance matrix reconstruction and mismatched steering vector compensation

机译:基于干扰协方差矩阵重建和失配转向矢量补偿的鲁棒自适应波束形成

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摘要

The performance of adaptive beamforming degrades in presence of signal model mismatches. In particular, when the desired signal is present in training snapshots, the adaptive beamforming is quite sensitive to desired signal steering vector mismatch. Therefore, a robust adaptive beamforming for actual system is proposed based on the reconstruction of interference covariance matrix and mismatched steering vector compensation. In the proposed method, the interference covariance matrix is firstly reconstructed by using Root-MUSIC method to estimate Direction-of-Arrival (DOA) of signals, where the desired signal component is removed from the training snapshots. Subsequently, the mismatched desired signal steering vector is compensated by solving a quadratically constrained quadratic programming problem. Simulation results show that the performance of proposed algorithm outperforms the existing robust adaptive beamforming, and the output signal-to-interference-plus-noise ratio (SINR) is close to optimal values. Therefore, the proposed algorithm could be significantly effective for actual system.
机译:在存在信号模型不匹配的情况下,自适应波束成形的性能会降低。特别地,当所需信号出现在训练快照中时,自适应波束成形对所需信号导引矢量失配非常敏感。因此,基于干扰协方差矩阵的重构和失配的转向矢量补偿,提出了一种针对实际系统的鲁棒自适应波束形成方法。在提出的方法中,首先使用Root-MUSIC方法重建干扰协方差矩阵,以估计信号的到达方向(DOA),然后从训练快照中删除所需的信号分量。随后,通过解决二次约束二次编程问题来补偿不匹配的期望信号操纵向量。仿真结果表明,所提算法的性能优于现有的鲁棒自适应波束形成,并且输出信噪比(SINR)接近最佳值。因此,所提出的算法对于实际系统可能是有效的。

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