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Compressive Sensing Approach for DOA Estimation Based on Sparse Arrays in the Presence of Mutual Coupling

机译:基于相互耦合存在的稀疏阵列的DOA估计压缩感测方法

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In the process of direction-of-arrival (DOA) estimation, the difference co-array of sparse arrays can achieve high degrees of freedom, which can be utilized to detect more signal sources than physical sensors based on spatial smoothing (SS) algorithm. In this paper, we present a method for DOA estimation using sparse signal recovery through compressive sensing (CS) approach in the presence of mutual coupling. Compared with SS algorithm, CS approach achieves a lower estimation error. Additionally, simulation results show that the estimation error of CS approach increases with the increase of mutual coupling. Also, it increases with the increase of the grid interval of the entire DOA space.
机译:在到达方向(DOA)估计的过程中,稀疏阵列的差异共同阵列可以实现高度的自由度,其可以用于基于空间平滑(SS)算法的物理传感器来检测更多的信号源。在本文中,我们通过在相互耦合的存在下,使用稀疏信号恢复使用稀疏信号恢复的DOA估计方法。与SS算法相比,CS方法实现了较低的估计误差。另外,仿真结果表明,随着相互耦合的增加,CS方法的估计误差增加。此外,它随着整个DOA空间的网格间隔的增加而增加。

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