This study proposes a robust wideband beamforming algorithm based on spectrum separation at divided subspaces to address the possible sensors array manifold deviations in practice. In this algorithm, an efficient sensors array manifold calibration approach based on subspace division is put forward and an improved interference-noise covariance matrix reconstruction approach based on spectrum separation is derived. The algorithm first divides the spatial space into several subspaces by Capon spatial spectrum and then calibrates array manifold deviations in these subspaces. Subsequently, the noise and interference information is extracted accurately after spectrum separation. Based on the extracted information, the optimal beamformer can be finally designed. Simulation results prove the excellent performance of the proposed algorithm in the presence of various array manifold deviation types and extents.

中文翻译：

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基于频谱子空间的宽带阵列鲁棒波束成形

这项研究提出了一种稳健的宽带波束成形算法，该算法基于在划分的子空间处的频谱分离，以解决实际中可能存在的传感器阵列歧管偏差。该算法提出了一种基于子空间划分的高效传感器阵列流形标定方法，并提出了一种基于谱分离的改进的干扰噪声协方差矩阵重建方法。该算法首先通过Capon空间谱将空间空间划分为几个子空间，然后在这些子空间中校准阵列流形偏差。随后，在分离频谱之后，准确地提取出噪声和干扰信息。基于提取的信息，可以最终设计出最佳的波束形成器。