声矢量阵导向最小方差波束形成算法研究

Acoustic vector-sensor array steered minimum variance beamforming

为了克服声压阵导向最小方差波束形成算法方位估计的左右模糊问题,提出了声矢量阵导向最小方差波束形成算法,指出了矢量阵导向矩阵与声压阵导向矩阵之间的关系.通过声压阵导向矩阵与单位矩阵的Kronecker积得到矢量阵的导向矩阵,从而使不同频率的矢量阵互谱密度矩阵聚焦.计算机仿真和海试实验证明与声压阵导向最小方差波束形成相比,矢量阵导向最小方差波束形成具有更好的方位分辨力且无左右模糊,并可以空间欠采样而不出现栅瓣.针对带宽内信噪比随频率变化的情况,用各频率的信噪比对导向协方差矩阵进行加权,改进了空间谱估计性能.

An acoustic vector-sensor array-steered minimum variance （VSTMV） beamforming method was proposed to overcome left-right ambiguity problems. The relationship between the steered matrix of an acoustic vector-sensor array and that of acoustic pressure-sensor array was demonstrated. The steered matrix of an acoustic vector-sensor array is obtained by the Kronecker product of the steered matrix of the acoustic pressure-sensor array and the unit matrix, thus focusing the cross spectral density matrix of vector-sensor array with different frequencies. Computer simulations and sea test results proved that, in comparison with steered minimum variance beamforming based on an acoustic pressure-sensor array, VSTMV beamforming gives better bearing resolution and results in unambiguous direction finding in all directions. Furthermore, no grating lobes were occurred if space under-sampling took place. Regarding the variation of signal to noise ratios with to the frequencies, a weight for the steered covariance matrix with the signal to noise ratio of each frequency can enhance the performance of spatial spectrum estimation.