论文部分内容阅读
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 underwater long-range direction finding, the method of acoustic vector subspace based on covariance matrix of sound pressure and vibration velocity is firstly discussed. Then, based on space-time virtual tap processing, a feature vector- Detection and subspace partition criteria. Theoretical analysis shows that, unlike the existing methods of direction finding based on the acoustic vector array, which process the vibration velocity information of the acoustic vector sensor as an independent array element, the new method of source number detection and bearing estimation is based on the combination of sound pressure and velocity information Processing, which can organically combine the high resolution of subspace method with the anti-noise ability of acoustic vector array, and achieve high-resolution detection and orientation of remote targets. The simulation experiment based on the lake test data proves the effectiveness of the method.