基于张量的互质面阵信号处理方法

doi:10.11959/j.issn.1000-436x.2020153

通信学报 ›› 2020, Vol. 41 ›› Issue (8): 99-109.doi: 10.11959/j.issn.1000-436x.2020153

基于张量的互质面阵信号处理方法

饶伟^1,²,桂宇风¹,李旦²

¹ 南昌工程学院信息工程学院，江西南昌 330099
² 复旦大学信息科学与工程学院，上海 200433

修回日期:2020-06-20 出版日期:2020-08-25 发布日期:2020-09-05
作者简介:饶伟（1982- ），男，江西乐安人，博士，南昌工程学院副教授、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|桂宇风（1995- ），男，江西新余人，南昌工程学院硕士生，主要研究方向为阵列信号处理等|李旦（1982- ），男，江苏常州人，博士，复旦大学副教授、硕士生导师，主要研究方向为信号处理及其在超声检测、图像、控制、测量和雷达中的应用等
基金资助:
江西省教育厅科研技术研究基金资助项目(GJJ170975);国家自然科学基金资助项目(61961025);国家自然科学基金资助项目(11974082)

Tensor-based approach to the co-prime planar array signal processing

Wei RAO^1,²,Yufeng GUI¹,Dan LI²

¹ School of Information Engineering,Nanchang Institute of Technology,Nanchang 330099,China
² School of Information Science and Technology,Fudan University,Shanghai 200433,China

Revised:2020-06-20 Online:2020-08-25 Published:2020-09-05
Supported by:
The Science Research Foundation of Jiangxi Provincial Education Department(GJJ170975);The National Natural Science Foundation of China(61961025);The National Natural Science Foundation of China(11974082)

摘要/Abstract

摘要：

针对由2个稀疏均匀矩形阵列（URA）构成的互质面阵（CPPA），提出了一种基于张量代数的阵列信号处理方法，以提高阵列自由度。首先，对CPPA中的2个URA进行拆分，将这2个URA的接收信号表示成2个张量；然后将其互相关结果处理成一个虚拟阵列的接收信号张量。分析表明，所提方法可将一个具有2 <sup>2</sup>L -1个物理阵元的 CPPA 转换成一个具有 $\frac{{(L + 1)}^{4}}{16}$ 个阵元的虚拟稀疏非均匀面阵。针对该虚拟面阵，给出了利用张量分解从其接收信号张量中估计入射信号二维波达角的方法，以避免二维谱峰搜索。与文献报道的互质面阵信号处理方法相比，所提方法将阵列自由度从L<sup>2</sup>提升至 $\frac{{(L + 1)}^{4}}{16} + 1$ ，并具有更好的信号波达角估计性能及较低的计算复杂度，仿真结果证明了所提方法的有效性。

关键词: 互质面阵, 二维波达角估计, 张量分解, 自由度

Abstract:

For the co-prime planar array (CPPA) consisting of two sparse uniform rectangular array (URA),a new processing method based on tensor algebra was proposed to enhance the degrees of freedom (DoF).By dividing each URA into some overlapping subarrays,the received signals of two URAs were expressed as two tensors.And then the cross-correlation between such two tensors was processed into a received signal tensor of the virtual array.Analysis show that by the new method,the CPPA with 2 ²L -1 physical elements can be transformed into a virtual sparse non-uniform planar array with $\frac{{(L + 1)}^{4}}{16}$ elements.For the virtual array,the tensor decomposition-based approach for estimating the two-dimensional (2-D) direction of arrival (DoA) of the incident signal is also proposed,which means 2-D spectral peak searching is avoided.Compared with the co-prime planar signal processing methods reported in the literature,the proposed method can increase the DoF from L ²to $\frac{{(L + 1)}^{4}}{16} + 1$ ,and has the better performance of the 2-D DoA estimation and lower computational complexity.Simulation results demonstrate the efficiency of the proposed method.

Key words: co-prime planar array, two-dimensional direction of arrival estimation, tensor decomposition, degree of freedom

中图分类号:

TN911.7

饶伟,桂宇风,李旦. 基于张量的互质面阵信号处理方法[J]. 通信学报, 2020, 41(8): 99-109.

Wei RAO,Yufeng GUI,Dan LI. Tensor-based approach to the co-prime planar array signal processing[J]. Journal on Communications, 2020, 41(8): 99-109.

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基于张量的互质面阵信号处理方法

Tensor-based approach to the co-prime planar array signal processing

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