基于奇异值分解的空域海杂波抑制算法  

Sea clutter suppression algorithm in spatial domain based on singular value decomposition

作　　者：王龙岗 岳显昌[1] 吴雄斌[1] 易先洲 WANG Longgang;YUE Xianchang;WU Xiongbin;YI Xianzhou(School of Electronic Information,Wuhan University,Wuhan 430072,China)

机构地区：[1]武汉大学电子信息学院,武汉430072

出　　处：《电波科学学报》2021年第4期645-652,共8页Chinese Journal of Radio Science

基　　金：国家自然科学基金(61771352);“十三五”国家重点研发计划(2016YFC1401100)。

摘　　要：为实现对高频地波雷达(high frequency surface wave radar,HFSWR)一阶海杂波谱中目标的检测,提出了基于奇异值分解(singular value decomposition,SVD)的空域海杂波抑制算法(简称空域SVD算法).空域SVD算法是利用海杂波较强的相关性,将邻近距离单元作为参考,对其阵列协方差矩阵进行SVD,估计空域的海杂波子空间和噪声子空间;再利用子空间的正交性,从阵列回波信号中去除其在海杂波子空间的投影分量,达到在空域抑制海杂波的目的.该方法与现有的空域海杂波抑制方法相比,不需要预先知道海杂波的方位,利用阵列协方差矩阵的SVD来估计子空间,使得子空间的估计比较容易且准确,提高了输出信杂噪比(signal to clutter plus noise ratio,SCNR),有利于目标的检测.In order to detect the targets in the first-order sea clutter spectrum of high frequency surface wave radar(HFSWR),a method based on singular value decomposition(SVD)is proposed to suppress sea clutter in spatial domain.The sea clutter suppression method is based on the strong correlation of sea clutter,thus we take the adjacent range bin as the reference.Then the sea clutter subspace and noise subspace in the spatial domain is estimated by singular value decomposition of its array covariance matrix.Finally,we subtract its projection in the sea clutter subspace from the array signal with the orthogonality of subspace,and achieves the purpose of suppressing sea clutter in the spatial domain.Compared with the existing methods of sea clutter suppression in spatial domain,there is no need to know the azimuth of sea clutter in advance.The subspace is estimated by singular value decomposition of its array covariance matrix,which makes it easier and more accurate to estimate the sea clutter subspace and noise subspace.The result shows that the method improves the signal to clutter plus noise ratio(SCNR),which is benefit to target detection.

关 键 词：高频地波雷达(HFSWR) 目标检测 奇异值分解(SVD) 空域 抑制海杂波 

分 类 号：TN957[电子电信—信号与信息处理]