基于未知互耦的机载STAP采样结构

Mingxin Liu, L. Zou, Xue-gang Wang
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引用次数: 1

摘要

在机载雷达的空时自适应处理(STAP)中,阵元之间的相互耦合会导致杂波协方差矩阵(CCM)估计不准确,从而导致雷达性能下降。为了解决这一问题,提出了一种新的基于协素数结构的STAP算法。该方法利用协素数结构和差分运算构造虚拟时空快照。因此,CCM是通过使用低秩矩阵恢复技术获得的这些虚拟快照来计算的。最后,构建虚拟权向量。仿真结果验证了该方法的有效性和优越性。该算法能有效地降低相互耦合效应,准确估计CCM,提高自由度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Airborne STAP with Unknown Mutual Coupling for Coprime Sampling Structure
In space-time adaptive processing (STAP) of airborne radar, the mutual coupling among array elements can lead to inaccurate estimation of the clutter covariance matrix (CCM), which makes the radar performance degradation. To solve this problem, a new STAP algorithm based on the coprime structure is developed. The proposed method uses the coprime structure and difference operation to construct the virtual space-time snapshots. Thus, the CCM is computed by utilizing these virtual snapshots obtained by using the low-rank matrix recovery technology. Finally, the virtual weight vector is built. The simulation results verify the effectiveness and superiority of the proposed method. The proposed algorithm can reduce the mutual coupling effect, accurately estimate CCM, and improve degrees of freedom (DOF).
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