基于声压振速联合处理的声矢量阵信源数检测与方位估计  

Detection of number of sources and direction of arrival estimation based on the combined information processing of pressure and particle velocity using acoustic vector sensor array

作　　者：白兴宇 姜煜 赵春晖[2] 

机构地区：[1]第七一五研究所,杭州310012 [2]哈尔滨工程大学信息与通信工程学院,哈尔滨150001

出　　处：《声学学报》2008年第1期56-61,共6页Acta Acustica

基　　金：高等学校优秀青年教师教学科研奖励计划(2001-226);水声技术国防科技重点实验室基金(OOJS23．8．1CB0104)资助项目

摘　　要：为解决水下远程测向问题,首先论述了基于声压与振速互协方差矩阵的声矢量阵特征子空间方法,然后利用空时虚拟抽头处理,提出了一种基于特征向量的信源数检测与子空间划分准则。理论分析表明,与现有的将声矢量传感器的振速信息作为独立阵元来处理的声矢量阵测向方法不同,新的信源数检测与方位估计方法完全基于声压与振速联合信息处理,能将子空间方法的高分辨能力与声矢量阵的抗噪能力有机结合起来,可实现对远程目标的高分辨检测与定向。基于湖试数据的仿真实验证明了所述方法的有效性。In order to solve the problem of DOA （direction of arrival） estimation of underwater remote targets, a novel subspace-decomposition method based on the cross covariance matrix of the pressure and the particle velocity of Acoustic Vector Sensor Arrays （AVSA） is proposed. Whereafter, using spatio-temporal virtual tapped-delay-line, a new eigenvector-based criteria of detection of number of sources and of subspace partition is also presented. The theoretical analysis shows that the new source detection and direction finding method is different from existing AVSA based DOA estimation methods using particle velocity information of Acoustic Vector Sensor （AVS） as an independent array element. It is entirely based on the combined information processing of pressure and particle velocity, has better estimation performance than existing methods in isotropic noise field. Computer simulations with data from lake trials demonstrate, the proposed method is effective and obviously outperforms existing methods in resolution and accuracy in the case of low signal-to-noise ratio （SNR）.

关 键 词：声矢量阵 检测 振速 方位估计 信源 联合处理 声压 联合信息处理 

分 类 号：TB567[交通运输工程—水声工程]