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Sparse DOD/DOA Estimation in a Bistatic MIMO Radar With Mutual Coupling Effect

机译:稀疏DOD / DOA估计在双面MIMO雷达中,具有相互耦合效果

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摘要

The unknown mutual coupling effect between antennas significantly degrades the target localization performance in the bistatic multiple-input multiple-output (MIMO) radar. In this paper, the joint estimation problem for the direction of departure (DOD) and direction of arrival (DOA) is addressed. By exploiting the target sparsity in the spatial domain and formulating a dictionary matrix with discretizing the DOD/DOA into grids, compressed sensing (CS)-based system model is given. However, in the practical MIMO radar systems, the target cannot be precisely on the grids, and the unknown mutual coupling effect degrades the estimation performance. Therefore, a novel CS-based DOD/DOA estimation model with both the off-grid and mutual coupling effect is proposed, and a novel sparse reconstruction method is proposed to estimate DOD/DOA with updating both the off-grid and mutual coupling parameters iteratively. Moreover, to describe the estimation performance, the corresponding Cramér⁻Rao lower bounds (CRLBs) with all the unknown parameters are theoretically derived. Simulation results show that the proposed method can improve the DOD/DOA estimation in the scenario with unknown mutual coupling effect, and outperform state-of-the-art methods.
机译:天线之间的未知互联效果显着降低了双面多输入多输出(MIMO)雷达中的目标定位性能。在本文中,解决了出发方向的联合估计问题和到达方向(DOA)。通过利用空间域中的目标稀疏性并将用分离DOD / DOA分散到网格中的字典矩阵,给出了基于压缩的感测(CS)的系统模型。然而,在实际的MIMO雷达系统中,目标不能精确地探测网格,并且未知的互联效果会降低估计性能。因此,提出了一种具有偏离电网和相互耦合效果的新型CS的DOD / DOA估计模型,提出了一种新的稀疏重建方法来估算DOD / DOA,并迭代地更新偏离电网和相互耦合参数。此外,为了描述估计性能,理论上派生了所有未知参数的相应Cramér⁻rao的下限(CRLBS)。仿真结果表明,该方法可以改善具有未知相互耦合效果的情况下的国防部/ DOA估计,以及优于最先进的方法。

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