声矢量圆阵宽带相干目标MVDR方位估计

针对宽带相干目标的远程探测问题,该文提出一种基于声压振速联合处理和矢量重构的声矢量圆阵MVDR波束形成方法。该方法利用相位模态变换技术,将声矢量圆阵变换为与信号频率无关的虚拟线阵,并构建虚拟线阵声压与组合振速的互协方差矩阵,利用声压与振速各分量间的空间相关性有效地抑制各向同性环境噪声;并对宽带相干信号的互协方差矩阵进行矢量重构,即将最大特征值对应的特征向量划分为相互重叠的子向量,从而构建前/后向Hermitian矩阵;最后,基于MVDR波束形成器实现宽带相干目标的方位估计。仿真计算和实验数据处理结果表明,该方法具较强的解相干能力和噪声抑制能力以及较高的方位估计性能。

MVDR beamforming for wideband coherent signals by using circular acoustic vector sensor arrays

This paper proposes a wideband minimum variance distortionless response (MVDR) beamforming for the direction-of-arrival (DOA) estimation of weak coherent signals by using uniform circular acoustic vector sensor arrays (UCAVSAs). This paper first uses the phase-mode transformation to covert the UCAVSA to a virtual linear array which is independent of the signal frequency. For eliminating the isotropic ambient noise, the correlation characteristics of the acoustic pressure and particle velocity are used to construct the cross-covariance matrix. Then, it is described that the eigenvector corresponding to the maximum eigenvalue of the wideband coherent signals in the virtual linear array contains all the DOA information of the signals. Based on this, this eigenvector is divided into overlapping subvectors to construct a forward/backward Hermitian matrix. Finally, the MVDR beamforming is used to estimate the DOAs. This method does not need to estimate the signal number. Simulation and experimental results show that the proposed algorithm has a stronger ability to suppress isotropic ambient noise, and it has a higher resolution and estimation accuracy.