复杂相干干扰场景下的稳健自适应波束形成器

Robust Adaptive Beamformer for Complex Coherent Interference Scenarios

  • 摘要: 自适应波束形成是一种有效的空域抗干扰方案。然而当接收中的多个不同来向的干扰间存在强相干性,一般的自适应波束形成算法无法获得与干扰子空间理想正交的权矢量,对相干干扰的理想抑制失效,残余干扰将大大影响处理结果用于目标检测和定位等的可靠性。针对在同时存在独立干扰和多组自相干干扰的复杂相干干扰场景下自适应波束形成的干扰抑制性能急剧恶化的问题,本文结合协方差矩阵重构思想和空间差分技术,提出了一种改进的自适应波束形成器。该波束形成器的构建基于最小方差无畸变响应波束形成器,首先利用Capon空间谱的功率估计重构了独立干扰+噪声协方差矩阵,获得在不受到接收信号中的期望信号的影响下对独立干扰实现理想抑制的波束形成权矢量;其次,利用空间差分技术重构了恢复相干干扰子空间信息的相干干扰协方差矩阵,进而得到对接收信号中的相干干扰实现理想抑制的波束形成权矢量;最后,结合以上两个权矢量推导出可对接收信号中的所有干扰实现同时抑制的波束形成器。仿真结果验证了提出的波束形成器在未知干扰DOA信息下仍可自适应获得精确的深干扰抑制零陷,同时具有低旁瓣特性,与现有算法相比展现出更佳的输出性能,且优势在小快拍和接收含期望信号时仍具有稳健性。此外,本文通过理论分析表明,有别于现有算法,提出的波束形成器在接收中的干扰数量大于阵列阵元数的场景下仍可获得理想的干扰抑制性能,并在仿真实验中设计典型场景验证了理论分析的正确性。

     

    Abstract: ‍ ‍Adaptive beamforming is an effective approach for suppressing interferences at the array receiver. However, when the interferences from the different direction-of-arrival (DOA) are strongly coherent, general adaptive beamformers cannot build the weight vector orthogonal to the interference subspace, thus resulting in the failure of optimal interference suppression. The residual interference significantly affects the array output’s reliability for subsequent processing, such as target detection and localization. A robust adaptive beamformer using interference covariance matrix reconstruction and the spatial differencing technique (SDT) is proposed to address the considerable performance degradation of general adaptive beamformers in a complex coherent interference scenario where uncorrelated interferences and multiple groups of self-coherent interferences coexist. Based on the minimum variance distortionless response (MVDR) beamformer, the algorithm first constructs the uncorrelated interference-plus-noise covariance matrix (UNCM) with Capon spectral power estimation and then applies the UNCM to the MVDR beamformer to obtain a modified weight vector for suppressing uncorrelated interferences. Second, using the SDT, a coherent interference covariance matrix (CICM) for restoring the actual coherent interference subspace is constructed, and then the modified weight vector for the ideal suppression of coherent interferences is obtained by applying the CICM to the MVDR beamformer. Finally, the proposed beamformer for simultaneous suppression of all interferences in the received signal is derived by combining the two weight vectors above. Simulation results confirm that the proposed beamformer can adaptively obtain accurate and deep interference nulling without DOA information and presents low sidelobes, thus reflecting its better interference suppression performance compared with existing algorithms. Additionally, the proposed beamformer is robust against small snapshots and high SNRs in the received signal. Results of theoretical analysis show that the proposed beamformer can achieve the ideal interference suppression performance even when the number of interferences exceeds that of array sensors, which is supported by the simulation for a typical design case.

     

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