一种宽带水声目标DOA估计方法  

A new direction of arrival estimation method for wideband underwater acoustic targets

作　　者：王彪[1] 陈峰[1] 何呈 戴跃伟[1] WANG Biao;CHEN Feng;HE Cheng;DAI Yuewei(School of Electronic and Information,Jiangsu University of Science and Technology,Zhenjiang 212003,China)

机构地区：[1]江苏科技大学电子信息学院,镇江212003

出　　处：《江苏科技大学学报（自然科学版）》2019年第1期51-56,共6页Journal of Jiangsu University of Science and Technology:Natural Science Edition

基　　金：国家自然科学基金资助项目(11574120;U1636117);江苏省自然科学基金资助项目(BK20161359)

摘　　要：针对现有的基于压缩感知的宽带水声目标DOA估计方法中存在估计计算时间长、失败率高的问题,将稀疏贝叶斯学习重构方法应用到宽带水声目标DOA估计中,采用定点方法对SBL算法中的核心超参量进行求解,提出一种基于稀疏贝叶斯学习的宽带水声目标DOA估计方法.通过仿真实验,验证了该方法的可行性与有效性,并证实该算法相对于常用的波束形成算法、MUSIC算法、SBL算法以及BP算法具有运算速度快、重构精度高等优点.The existing direction of arrival (DOA) estimation methods for wideband underwater acoustic target based on CS have longer computation time and higher estimation failure rates. To solve these problems, a new direction of arrival estimation algorithm of wideband underwater acoustic target based on sparse Bayesian learning is proposed, which uses sparse Bayesian learning as the reconstructing algorithm to DOA estimation for wideband underwater acoustic target and employs fixed-point method to obtain the value of core hyperparameter to estimate the DOA. Simulation results verify the feasibility and effectiveness of the proposed algorithm and confirm this algorithm had advantages of high speed for the process of computation and superior recovery performance to common beamforming algorithm, MUSIC algorithm, and normative SBL method with BP algorithm.

关 键 词：DOA估计 压缩感知 宽带 稀疏贝叶斯学习 定点方法 

分 类 号：TN911[电子电信—通信与信息系统]