基于联合距离角稀疏恢复和波束形成的分布式阵列雷达DRFM中继器干扰抑制方法

Remote. Sens. Pub Date : 2023-07-07 DOI:10.3390/rs15133449
B. Han, X. Qu, Xiaopeng Yang, Zhengyan Zhang, Wolin Li
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引用次数: 1

摘要

分布式阵列雷达具有较高的角分辨率和测量精度,为抑制数字射频存储器(DRFM)中继器干扰提供了一种解决方案。然而,由于分布式雷达孔径较大,远场平面波假设不再满足。传统的自适应波束形成方法由于方向矢量不匹配而不能有效地工作。针对这一问题,本文提出了一种基于距离角稀疏恢复和波束形成联合抑制分布式阵列雷达DRFM中继器干扰的方法。首先,根据近场条件下的球面波模型重构分布式阵列的转向矢量;然后,利用重构的转向向量生成联合距离角稀疏字典,利用加权l1范数奇异值分解(W-L1-SVD)算法估计干扰距离角位置;最后,基于线性约束最小方差(LCMV)算法实现了距离角联合零化波束形成,以抑制干扰。在实际的地面分布式阵列雷达系统上进行了仿真和实验,验证了该方法的性能和有效性。
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DRFM Repeater Jamming Suppression Method Based on Joint Range-Angle Sparse Recovery and Beamforming for Distributed Array Radar
Distributed array radar achieves high angular resolution and measurement accuracy, which could provide a solution to suppress digital radio frequency memory (DRFM) repeater jamming. However, owing to the large aperture of a distributed radar, the far-field plane wave assumption is no longer satisfied. Consequently, traditional adaptive beamforming methods cannot work effectively due to mismatched steering vectors. To address this issue, a DRFM repeater jamming suppression method based on joint range-angle sparse recovery and beamforming for distributed array radar is proposed in this paper. First, the steering vectors of the distributed array are reconstructed according to the spherical wave model under near-field conditions. Then, a joint range-angle sparse dictionary is generated using reconstructed steering vectors, and the range-angle position of jamming is estimated using the weighted L1-norm singular value decomposition (W-L1-SVD) algorithm. Finally, beamforming with joint range-angle nulling is implemented based on the linear constrained minimum variance (LCMV) algorithm for jamming suppression. The performance and effectiveness of proposed method is validated by simulations and experiments on an actual ground-based distributed array radar system.
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