最小方差谱估计算法的改进及应用  

Improvement of MVM in high-resolution shallow water bathymetric side-scan sonar system

作　　者：胡隽[1] 

机构地区：[1]中国科学院声学研究所海洋声学技术实验室,北京100080

出　　处：《计算机工程与应用》2007年第23期187-190,共4页Computer Engineering and Applications

基　　金：国家高技术研究发展计划(863)(the National High- Tech Research and Development Plan of China under Grant No.2005AA611020)

摘　　要：最小方差谱估计方法(MVM)是声纳信号波达方向估计中一种十分重要的方法,然而工程实际应用中在小快拍数和低信噪比的场合最小方差谱估计方法的估计性能会受到很大影响。提出的基于时空相关信号协方差矩阵的最小方差谱估计算法(MVMBased on Time-Space Correlation Matrix)利用噪声在空间和时间上的相关性比较弱的特点大大改善了MVM在小快拍数和低信噪比场合的估计性能。基于时空相关信号协方差矩阵的最小方差谱估计算法应用到浅水高分辨率测深侧扫声纳的波达方向估计中,取得了比原始信号协方差矩阵的最小方差谱估计算法更好的效果。算法中的时空相关信号协方差矩阵构成方法在波达方向估计中有广泛的应用价值。MVM is a very important DOA finding method of DOA estimation technology.But when the number of snapshots is small and signal noise ratio is low,the performance of MVM deteriorates very fast.A novel DOA finding method--MVM Based on Time-Space Correlation Matrix is presented to improve the DOA finding performance.MVM Based on Time-Space Correlation Matrix exploits properties of noise to enhance the performance of MVM in the way which could be applied widely in DOA finding methods.When MVM Based on Time-Space Correlation Matrix is applied in high-resolution shallow water bathymetric side-scan sonar system,the DOA estimation could be achieved with less error.

关 键 词：波达方向估计 最小方差谱估计算法 时空相关协方差矩阵 

分 类 号：TN911.23[电子电信—通信与信息系统]