阵列信号降采样低秩矩阵的恢复方法

doi:10.3969/j.issn.1001-2400.2014.05.006

Abstract

Abstract:

Matrix Completion (MC) theory can recover the under-sampled data in the array signal processing, further estimating the direction of arrival (DOA) as the fully sampled data does. However, it is required that the data should be under-sampled randomly in different snapshots which satisfy the randomness of MC theory. When some sensors are unsampled or broken in the whole observing time, the previous method would fail. To address this problem, a new processing method is proposed in this paper. The inner relationship among sensors is used, and then we reshape the signal vector in a single snapshort into an equivalent low-rank matrix, which can be recovered effectively by minimizing the nuclear norm. Simulation results validate the effectiveness of the proposed method. Meanwhile, the method can lower the noie power, and improve the performance of the DOA.

Key words: array signal processing, matrix completion, low rank matrix, direction of arrival

YANG Dong;LIAO Guisheng;ZHU Shengqi;WANG Kai. Improved low-rank recovery method for sparsely sampling data in array signal processing[J].J4, 2014, 41(5): 30-35.

References

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Improved low-rank recovery method for sparsely sampling data in array signal processing

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