三维稀疏阵列及其基于耦合张量分解的DOA估计

罗中华; 左富豪; 樊棠怀; 饶伟

doi:10.11959/j.issn.1000-436x.2025112

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三维稀疏阵列及其基于耦合张量分解的DOA估计

学术通信 | 更新时间：2025-07-04

- 三维稀疏阵列及其基于耦合张量分解的DOA估计
- 3D sparse array and its DOA estimation based on coupled tensor decomposition
- 通信学报 2025年46卷第6期页码：270-284
- 作者机构：
  
  1.南昌理工学院电子信息工程学院，江西南昌 330044
  2.南昌工程学院信息工程学院，江西南昌 330099
- 作者简介：
  
  [ "罗中华（1971- ），男，江西南昌人，南昌理工学院教授，主要研究方向为通信与信息系统。" ]
  [ "左富豪（1999- ），男，河南周口人，南昌工程学院硕士生，主要研究方向为阵列信号处理。" ]
  [ "樊棠怀（1962- ），男，江西修水人，博士，南昌理工学院教授，主要研究方向为信息获取与处理。" ]
  [ "饶伟（1982- ），男，江西乐安人，博士，南昌工程学院教授、硕士生导师，主要研究方向为阵列信号处理、自适应信号处理。" ]
- 基金信息：
  
  国家自然科学基金资助项目(62463021)
- DOI：10.11959/j.issn.1000-436x.2025112
  中图分类号： TN911.7
- 收稿日期：2025-02-07，
  
  修回日期：2025-06-05，
  
  纸质出版日期：2025-06-25
- 稿件说明：
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罗中华,左富豪,樊棠怀等.三维稀疏阵列及其基于耦合张量分解的DOA估计[J].通信学报,2025,46(06):270-284.

LUO Zhonghua,ZUO Fuhao,FAN Tanghuai,et al.3D sparse array and its DOA estimation based on coupled tensor decomposition[J].Journal on Communications,2025,46(06):270-284.
罗中华,左富豪,樊棠怀等.三维稀疏阵列及其基于耦合张量分解的DOA估计[J].通信学报,2025,46(06):270-284. DOI： 10.11959/j.issn.1000-436x.2025112.

LUO Zhonghua,ZUO Fuhao,FAN Tanghuai,et al.3D sparse array and its DOA estimation based on coupled tensor decomposition[J].Journal on Communications,2025,46(06):270-284. DOI： 10.11959/j.issn.1000-436x.2025112.

摘要

为提高信号二维波达方向（DOA）估计性能，提出了一种三维稀疏阵列结构及其基于耦合张量分解的DOA估计方法。利用子阵信号的二阶统计量构建了一个虚拟的、在

轴方向阵元呈稀疏分布的“十”字形立体阵。分析表明，当阵列使用

https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=84332000&type=

6.77333355

https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=84332016&type=

19.47333336

（

为大于2的奇数）个物理阵元时，其对应的虚拟阵在

和

轴方向的阵列孔径均为(

-1)

，在

轴方向的阵列孔径为(

)

。为充分利用虚拟阵的大孔径来提升信号DOA估计性能，并消除

轴方向阵元间距大于

而引起的相位模糊，提出了借助耦合张量分解解决相位模糊并实现DOA估计的方法。理论分析和仿真结果表明，在相同的物理阵元数下，相较于现有三维阵列，由于新方法具有更大的阵列孔径从而具有更优的估计性能。

Abstract

To improve the performance of two-dimensional direction-of-arrival (DOA) estimation of signals

a three-dimensional sparse array structure and its coupled tensor decomposition-based DOA estimation method was proposed. By utilizing the second-order statistics of the signals from these subarrays

a virtual three-dimensional cross array was constructed

where the element spacing in the

-axis direction was sparse. Analysis showed that when

https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=84332039&type=

6.77333355

https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=84332002&type=

19.47333336

(where

was an odd number greater than 2) physical elements were used in the array

the corresponding virtual array possessed an aperture of (

-1)

in the

-axis and

axis directions and (

)

in the

-axis direction. To fully exploit the large array aperture of the virtual array for enhancing DOA estimation performance and eliminating phase ambiguity caused by the element spacing greater than

in the

-axis direction

a method using coupled tensor decomposition for resolving phase ambiguity and achieving DOA estimation was developed. Theoretical analysis and simulation results demonstrate that

when the number of physical elements used in arrays is identical

the proposed method can yield a better estimation performance than existing three-dimensional arrays

because it has a larger array aperture.

关键词

Keywords

references

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