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Sparse-based direction finding in MIMO radar with mutual coupling

机译:基于稀疏的方向在MIMO雷达中找到了相互耦合的

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摘要

In this study, an estimation problem for target directions in the multiple-input and multiple-output (MIMO) radar system with unknown mutual coupling is considered. To exploit the target sparsity in the spatial domain, a compressed sensing-based method using multiple measure vectors is proposed to reconstruct the sparse targets and estimate the target directions and scattering coefficients. Additionally, we also propose an iterative method to estimate the mutual coupling matrices after obtaining the target information, where the sub-gradients are derived theoretically to update the mutual coupling matrices. Simulation results show that compared with the exiting methods, the better estimation performance for both target directions and mutual coupling matrices can be achieved by the proposed method.
机译:在该研究中,考虑了多输入和多输出(MIMO)雷达系统中的目标方向的估计问题。为了利用空间域中的目标稀疏性,提出了一种使用多个度量向量的基于压缩的基于传感的方法来重建稀疏目标并估计目标方向和散射系数。另外,我们还提出了一种迭代方法来估计在获得目标信息之后估计互联耦合矩阵,其中从理论上导出子梯度以更新相互耦合矩阵。仿真结果表明,与退出方法相比,可以通过所提出的方法实现针对目标方向和互联耦合矩阵的更好的估计性能。

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