降维的四阶累量近场信源定位方法  

Dimension Reduced Fourth-Order Cumulant Near-Field Source Localization Method

作　　者：李宛儒 邓科[1] 殷勤业[1] 张雁 LI Wanru;DENG Ke;YIN Qinye;ZHANG Yan(Faculty of Electronic and Information Engineering,Xi’an Jiaotong University,Xi’an 710049,China;Information and Communications Company,State Grid Shaanxi Electric Power Company,Xi’an 710048,China)

机构地区：[1]西安交通大学电子与信息学部,西安710049 [2]国网陕西省电力公司信息通信公司,西安710048

出　　处：《数据采集与处理》2023年第6期1257-1267,共11页Journal of Data Acquisition and Processing

基　　金：国家自然科学基金(62171364);国网陕西省电力公司科技项目(5226XT190006)。

摘　　要：针对近场信源定位中自由度小、准确性低等问题,提出一种基于四阶累量矩阵的定位算法。首先构造等效导向矢量包含波达方向(Direction of arrival,DOA)和距离信息的高维虚拟协方差矩阵,在角度估计中,提出基于矩阵秩亏来搜索最小奇异值倒数的一维搜索方法,降低了计算量,在增大自由度的同时利用高斯噪声高阶累量为零的特性提高了低信噪比下的性能;在不进行额外计算的前提下,直接利用角度估计中进行奇异值分解时得到的奇异向量所包含的距离信息,通过最小二乘法得到距离。仿真结果表明,相比于已有算法,该方法可以仅在一个高阶累量矩阵中通过一维搜索估计角度和距离,在降低复杂度的同时提高了准确性,并且提出方法的自由度是降维多重信号分类方法的2倍。For the problems of low degree of freedom and low accuracy in near-field source localization,a localization algorithm based on fourth-order cumulant matrix is proposed.Firstly,a high-dimensional virtual covariance matrix is constructed,where the equivalent steering vector contains both direction of arrival(DOA)and distance information.In angle estimation,a one-dimensional search method based on rank deficiency to search the reciprocal of the minimum singular value is proposed,where the computational burden is reduced.The degrees of freedom are increased and the characteristic that the high-order cumulant of Gaussian noise is zero is exploited to improve the estimation performance at low signal-to-noise ratio.In the estimation of distance,the distance information contained in the singular vector obtained by singular value decomposition in angle estimation can be directly exploited without additional calculation,and the distance is estimated by the least square method.Simulation results show that the method estimates the angle and distance information of the near-field source through the one-dimensional search only in a high-order cumulant matrix,which reduces the computational burden and improves the accuracy of the estimation compared with the existing algorithms.Moreover,the proposed method has twice as many degrees of freedom as the reduced-dimension MUSIC method.

关 键 词：阵列信号处理 近场信源 四阶累积量 一维搜索 最小二乘法 

分 类 号：TN911[电子电信—通信与信息系统]