基于耦合张量分解的稀疏阵列二维DOA估计算法  

DOA estimation algorithm with two-dimensional sparse array based on coupling tensor decomposition

作　　者：任明健 胡国平[1] 周豪[1] 游致远 张凌培 REN Mingjian;HU Guoping;ZHOU Hao;YOU Zhiyuan;ZHANG Lingpei(Air Defense and Missile Defense College,Air Force Engineering University,Xi’an 710038,China;Graduate School,Air Force Engineering University,Xi’an 710038,China;Unit 95517 of the PLA,Chengdu 610000,China)

机构地区：[1]空军工程大学防空反导学院,陕西西安710038 [2]空军工程大学研究生院,陕西西安710038 [3]中国人民解放军95517部队,四川成都610000

出　　处：《系统工程与电子技术》2023年第4期958-964,共7页Systems Engineering and Electronics

基　　金：国家自然科学基金(62071476)资助课题。

摘　　要：传统基于张量分解的稀疏阵列波达方向(direction of arrival,DOA)估计,通常将协方差矩阵直接进行划分来构建满秩张量,但这种方法没有考虑数据间的结构信息,使得信息利用不充分。针对这一问题,提出了一种基于数据间耦合关系的张量分解算法。根据信息间的结构特点,构建在俯仰和方位维度能分别利用耦合特性的两个三阶张量。通过张量分解从中估计出两组角度值,将其中利用耦合特性估计出的角度值作为DOA值,伴随产生的估计值用作角度匹配。仿真结果验证了所提算法可进一步提升对数据间耦合信息的利用,有效提高二维DOA估计的精度。The traditional sparse array direction of arrival(DOA)estimation based on tensor decomposition usually divides the covariance matrix directly to construct the full rank tensor,but this method does not consider the structural information between data,which makes the information underutilized.To solve this problem,an improved tensor decomposition algorithm based on the coupling relationship between data is proposed.According to the structural characteristics of information,two third-order tensors which can use the coupling characteristics in elevation and azimuth dimensions are constructed.Two sets of angle values are estimated by tensor decomposition.The angle value estimated by using the coupling characteristics is used as the DOA value,and the accompanying estimated value is used as the angle matching.Simulation results show that the proposed algorithm can further improve the utilization of coupling information between data and effectively improve the accuracy of two-dimensional DOA estimation.

关 键 词：耦合张量 稀疏阵列 波达方向估计 

分 类 号：TN953[电子电信—信号与信息处理]