A Matched Field Processing Based on Compressed Sensing

被引：0

作者：

Chen, Yingchun ^{[1
]}

Jiang, Yali ^{[1
]}

Wang, Biao ^{[1
]}

机构：

[1] Jiangsu Univ Sci & Technol, Dept Elect Informat Engn, Zhenjiang, Jiangsu, Peoples R China

来源：

PROCEEDINGS OF THE ADVANCES IN MATERIALS, MACHINERY, ELECTRICAL ENGINEERING (AMMEE 2017) | 2017年 / 114卷

关键词：

Underwater Acoustic Localization; Compressed Sensing; Matched Field Processing; Sparse Reconstruction;

D O I：

暂无

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

The traditional MFP (matched field processing, MFP) methods of underwater acoustic target often have poor estimation performance or get inaccurate estimation result on the constrain of spatial sparse observation. Considering the problem, this paper proposed a new high-accuracy MFP estimation algorithm of underwater acoustic target based on compressed sensing by analyzing the space sparsity of underwater target location. The algorithm established the spatial sparse description model of underwater target, and compressed sensing the underwater target in spatial domain, then used the joint sparse reconstruction algorithm to achieve the MFP estimation of underwater acoustic target. The simulation results show that the method can increase the DOA estimation accuracy of underwater acoustic target at less array elements and less snapshots.

引用

页码：254 / 258

页数：5