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基于累量的近场源快速定位算法
引用本文:张红楠,邓科,殷勤业. 基于累量的近场源快速定位算法[J]. 信号处理, 2021, 37(11): 2106-2114. DOI: 10.16798/j.issn.1003-0530.2021.11.011
作者姓名:张红楠  邓科  殷勤业
作者单位:西安交通大学信息与通信工程学院
基金项目:国家自然科学基金资助项目(61941118)
摘    要:本文提出了一种基于累量的近场源参数快速估计方法。具体地,本文首先构造了一个累量矩阵,对其进行奇异值分解后,利用得到的右奇异向量和左奇异向量分别使用类Root-MUSIC方法得到了近场波达方向和距离估计的闭式解。该方法利用高阶累量矩阵,减少了阵列孔径损失,提高了能分辨的最大信源数,而且与其他基于高阶累积量的方法相比,该方法在近场的波达方向与距离的估计过程中只需要构造一个累量矩阵和进行一次奇异值分解,并且使用闭式解完全避免了峰值搜索,大大降低了运算量,同时还提高了估计的分辨概率和精度。此外,该方法在几乎没有增加额外计算量的情况下可以推广到混合场源的情况。仿真结果表明,该算法的分辨率和精度都有较大的优越性。 

关 键 词:快速参数估计   近场源   累量矩阵   闭式解
收稿时间:2021-02-18

Fast near field source localization algorithm based on Cumulant
Affiliation:School of Information and Communication Engineering, Xi’an Jiaotong University
Abstract:In this paper, a new fast parameter estimation method based on cumulant is proposed for near-field sources. Firstly, a cumulant matrix is constructed and its singular value decomposition (SVD) is performed. Secondly, the closed form solutions of direction-of-arrival (DOA) and distance are obtained through the Root-MUSIC method from its left and right singular vectors, respectively. By exploiting the high-order cumulant matrix, we reduce the array aperture loss and improves the maximum number of sources that can be distinguished. Compared with other methods based on the high-order cumulants, our proposed method constructs only one cumulant matrix and performs singular value decomposition (SVD) only once, obtaining the closed form solution which completely avoids the peak search. As a result, the computation burden is greatly reduced, and the resolution probability and accuracy of the estimation are improved. Furthermore, our method can be applied in the mixed field sources without much additional computational burden. The simulation results show the better resolution and accuracy of our method. 
Keywords:
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