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Robust Capon Beamforming in the Presence of Mismatches

机译:存在失配时的鲁棒Capon波束成形

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摘要

Provided that the array steering vector corresponding to the signal of interest is accurately known, the Capon beamformer has better resolution and much better interference rejection capability than the data-independent beamformer. However, when mismatches between the actual and presumed array responses to the desired signal may frequently occur in practical situations, the performance of the Capon beamformer is known to degrade substantially. The similar type of performance degradation can occur when the signal steering vector is known exactly but the training sample size is small. In this paper, we propose a novel approach to robust Capon beamforming. The proposed robust Capon beamformer provides excellent robustness against some types of mismatches, offers faster convergence rate and makes the mean output array SINR consistently close to the optimal one. Computer simulations show better performance of our proposed robust Capon beamformer than that of the standard Capon beamformer.
机译:假设准确地知道了与感兴趣信号相对应的阵列导引矢量,Capon波束形成器比独立于数据的波束形成器具有更好的分辨率和更好的抗干扰能力。但是,在实际情况下,当实际信号和假定阵列响应对所需信号的不匹配可能经常发生时,已知Capon波束形成器的性能会大大降低。当确切知道信号控制向量但训练样本量较小时,可能会发生类似类型的性能下降。在本文中,我们提出了一种新颖的鲁棒Capon波束成形方法。所提出的鲁棒性的Capon波束形成器针对某些类型的失配提供了出色的鲁棒性,提供了更快的收敛速度,并使平均输出阵列SINR始终接近最佳值。计算机仿真表明,与标准Capon波束形成器相比,我们提出的鲁棒Capon波束形成器具有更好的性能。

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