利用海洋环境噪声互相关实现阵形校准

阵列信号处理需要准确的阵形,然而海底水平阵的阵形很难精确测量。利用海洋环境噪声可以提取两点间的格林函数,这为无源校准阵形提供了新的可能。通过海洋环境噪声互相关叠加可以获取两个阵元之间的距离信息,一种方法是可以通过该距离与位置之间的关系构建非线性方程组并利用最小二乘法(LS)求解阵形。本文利用多维尺度变换法(MDS)求解,通过对度量矩阵的特征值分解获得阵形。数值仿真和实验数据证明了该方法的可行性,并且MDS相比于LS有更稳健的性能。

Using ambient noise cross correlation for array self-localization

An accurate array manifold is necessary for array signal processing.However,it is difficult to measure the positions of the horizontal array elements on ocean bottom.Extracting the empirical Green's function from ambient noise provides an alternative to calculate the array element positions passively.The distance between two array elements can be obtained from the superimposed cross-correlation functions.One way is to build the nonlinear overdetermined equations,and solve the question by the Least Square(LS) method.This paper uses a method called MultiDimensional Scaling(MDS) to deal with this issue.It constructs the Gram matrix of position vector,and acquire the array shape by the eigenvalue decomposition of Gram matrix.Numerical simulations and experimental results verify the effectiveness of MDS and show that MDS is more robust than LS.