一种新的声矢量阵最小范数算法

A new mini-norm algorithm based on the acoustic vector sensor array

现有的声矢量阵方位估计算法基本都是将声矢量传感器(AVS)的振速信息作为与声压相同的独立阵元信息来处理,没有充分利用AVS中声压和振速的相干性,以及由此带来的抗各向同性噪声能力.基于AVS中声压和振速的相干性原理,提出了一种新的声矢量阵最小范数算法.新算法充分利用了AVS中声压和振速联合信息处理的优势,能更好地将最小范数(MN)算法的高分辨能力与AVS的抗噪能力有机地结合起来,实现远程高分辨DOA估计.理论分析和基于湖试数据的仿真实验证明了所提算法的有效性.

Proposed is a new mini-norm algorithm based on the acoustic vector sensor array （AVSA）. It is different from existing AVSA-based direction of arrival （DOA） estimation algorithms using particle velocity information of acoustic vector sensor （AVS） as an independent array element. The new mini-norm algorithm is based on the principle of coherency between pressure and particle velocity and has better DOA estimation performance than existing algorithms in isotropic noise field. Theoretical analysis and computer simulations based on real data show that the proposed algorithm is effective and outperforms existing algorithms in resolution and accuracy in the case of low signal-to-noise ratio （SNR）.