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Two-Dimensional DOA Estimation with Partial Damaged Sensors in Rectangular Array Based on Tensor Reconstruction

机译:基于张量重构的矩形阵列中带有局部损伤传感器的二维DOA估计

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In the field of direction of arrival (DOA) estimation, there exists no problem of angle merging and it has low sidelobe characteristics with the uniform rectangular array. But when sensors in the uniform rectangular array are partially damaged, the two-dimensional DOA estimation performance of the original algorithms will seriously decline, and even have a performance failure in some cases. To solve the problem, we study the inexact augmented Lagrange multiplier method (IALM). Through utilizing features of low-rank matrix, obtained by the tensor unfolding in different modes, in the tensor model of the received signal, we propose the IALM-ESPRIT algorithm. Compared with the direct ESPRIT algorithm, the performance of two-dimensional DOA estimation is significantly improved when partial sensors damaged.
机译:在到达方向(DOA)估计领域,不存在角度合并问题,并且具有均匀矩形阵列的低旁瓣特性。但是,当均匀矩形阵列中的传感器部分损坏时,原始算法的二维DOA估计性能将严重下降,甚至在某些情况下会出现性能故障。为了解决该问题,我们研究了不精确的增强拉格朗日乘数法(IALM)。通过利用不同模式下张量展开获得的低秩矩阵特征,在接收信号的张量模型中,提出了IALM-ESPRIT算法。与直接ESPRIT算法相比,当部分传感器损坏时,二维DOA估计的性能显着提高。

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