非高斯噪声下互质阵压缩感知目标方位估计  

Target direction estimation using coprime array compressive sensing under non-Gaussian noise

作　　者：苏杨旭 周胜增[1] 张昌[1] 曾赛[1] SU Yangxu;ZHOU Shengzeng;ZHANG Chang;ZENG Sai(Shanghai Institute of Ship Electronic Equipment,Shanghai 201100,China)

机构地区：[1]上海船舶电子设备研究所,上海201100

出　　处：《声学技术》2025年第1期21-28,共8页Technical Acoustics

摘　　要：在进行目标方位(direction of arrival,DOA)估计时,背景噪声通常被假定为高斯噪声,但在水声环境中,噪声的概率密度函数存在非高斯分布情况,这会造成DOA估计出现伪峰及背景噪声增大等问题。文章将不服从高斯分布的水下噪声建模为α稳定分布,采用数据加权的方法对信号进行预处理,随后在互质阵列中应用压缩感知方法对宽带信号进行目标DOA估计。对8元互质阵列使用改进算法进行仿真,结果表明该方法可以准确做出DOA估计,同时减少了伪峰数量。湖试数据的处理结果表明,在互质阵列中基于数据加权的压缩感知DOA估计能够减少伪峰,增强目标检测能力,具有更好的检测效果及实用性。In the direction of arrival(DOA)estimation,the background noise is usually assumed to be Gaussian noise.However,in underwater acoustic environments,the probability density function(PDF)of the noise has a non-Gaussian distribution,which leads to false peaks and background noise in DOA estimation.In this paper,underwater noise that does not follow Gaussian distribution is modeled as anα-stable distribution,and data weighting is used to preprocess the signal.Then compressive sensing method is applied in a coprime array to estimate the DOA of a broadband signal.Simulations are conducted on an 8-element coprime array with improved algorithm,and the results show that the method can accurately estimate DOA while reducing the number of pseudo peaks.The processing results of lake test data show that compressed sensing DOA estimation based on data weighting in coprime arrays can reduce false peaks,enhance target detection capability,and have better effectiveness and practicality.

关 键 词：目标方位估计 数据加权 互质阵列 Α稳定分布 

分 类 号：TN911.7[电子电信—通信与信息系统]