互质阵列信号处理研究进展：波达方向估计与自适应波束成形

周成伟; 郑航; 顾宇杰; 王勇; 史治国

doi:10.12000/JR19068

互质阵列信号处理研究进展：波达方向估计与自适应波束成形

doi: 10.12000/JR19068

周成伟^1,,
郑航^2,,
顾宇杰^3,,
王勇²,
史治国^2, ,

1.
浙江大学控制科学与工程学院杭州 310027
2.
浙江大学信息与电子工程学院杭州 310027
3.
天普大学电子与计算机工程系费城 19122

基金项目: 中国博士后科学基金(2018M642431, 2019T120515)，国家自然科学基金(61772467)，浙江省杰出青年科学基金(LR16F010002)，中央高校基本科研业务费专项资金(2019FZA5006)

详细信息

作者简介:
周成伟(1990–)，男，浙江临海人，博士，助理研究员。2018年6月在浙江大学信息与电子工程学院获得工学博士学位，现为浙江大学控制科学与工程学院博士后、助理研究员。研究方向为阵列信号处理、波达方向估计、波束成形。E-mail: zhouchw@zju.edu.cn

郑　航(1998–)，男，广东汕头人，浙江大学在读研究生。2019年于同济大学获得工学学士学位，现于浙江大学电子科学与技术专业攻读硕士学位。研究方向为阵列信号处理。E-mail: hangzheng@zju.edu.cn

顾宇杰(1980–)，男，江苏如东人，博士，副研究员。2008年在浙江大学信息与电子工程学系获得博士学位，现为美国天普大学电子与计算机工程系研究员。研究方向为统计与阵列信号处理，压缩感知，波形设计，自适应波束成形等。E-mail: guyujie@hotmail.com

王　勇(1974–)，男，河南郏县人，博士，副教授，2002年3月在浙江大学信息与电子工程学系取得博士学位。现为浙江大学信电学院副教授。研究方向为雷达信号识别技术，超宽带应用技术。E-mail: wangy@zju.edu.cn

史治国(1978–)，男，江苏扬州人，博士，教授。2006年3月在浙江大学信息与电子工程学系获得博士学位，现为浙江大学信息与电子工程学院教授、博士生导师。主要研究方向为信号处理、物联网、群智感知。E-mail: shizg@zju.edu.cn

通讯作者:
史治国　shizg@zju.edu.cn

责任主编：张小飞 Corresponding Editor: ZHANG Xiaofei
中图分类号: TN911.7
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出版历程
- 收稿日期: 2019-07-12
- 修回日期: 2019-10-11
- 网络出版日期: 2019-10-01

Research Progress on Coprime Array Signal Processing: Direction-of-Arrival Estimation and Adaptive Beamforming

ZHOU Chengwei^1
,,
ZHENG Hang^2
,,
GU Yujie^3
,,
WANG Yong²,
SHI Zhiguo^{2
, ,}

1.
College of Control Science and Engineering, Zhejiang University, Hangzhou 310027, China
2.
College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310027, China
3.
Department of Electrical and Computer Engineering, Temple University, Philadelphia, PA 19122, USA

Funds: The China Postdoctoral Science Foundation (2018M642431, 2019T120515), The National Natural Science Foundation of China (61772467), Zhejiang Provincial Natural Science Foundation of China (LR16F010002), The Fundamental Research Funds for Central Universities (2019FZA5006)

More Information

Corresponding author: SHI Zhiguo, shizg@zju.edu.cn

摘要

摘要: 阵列信号处理是雷达领域各类应用的核心技术之一。近年来，互质阵列的提出打破了传统方法受限于奈奎斯特采样速率这一瓶颈，其稀疏布设的阵列结构和互质欠采样的信号处理方式大幅降低了系统所需的软硬件开销，为当前不断提升的实际应用需求提供了理论基础和技术前提。鉴于其在自由度、分辨率及计算复杂度等方面的性能优势，互质阵列信号处理的理论和技术研究受到了国内外学者的广泛关注。该文分别从波达方向估计和自适应波束成形这两个阵列信号处理领域的基本问题出发，介绍了互质阵列信号处理方向的研究进展。在互质阵列波达方向估计方面，该文总结了互质子阵分解方法和虚拟阵列信号处理方法等两类典型技术路线，并以此为基础介绍了压缩感知和无网格化技术在低复杂度和超分辨估计等方面的最新研究工作。在互质阵列波束成形方面，该文剖析了其与互质阵列波达方向估计问题的区别与联系，并介绍了面向互质阵列的高效鲁棒自适应波束成形设计方法。该文旨在通过对互质阵列信号处理研究前沿的分类归纳和总结，探讨各类方法的优势和未来的研究方向，为其在雷达等领域的产业需求和实际应用提供理论和技术参考。
- 阵列信号处理 /
- 互质阵列 /
- 波达方向估计 /
- 自适应波束成形
Abstract: Array signal processing is an essential tool in broad radar applications. The coprime array has recently been proposed to overcome the bottleneck caused by the Nyquist spatial sampling rate. The coprime array, whose sparse structure and undersampling feature drastically decrease necessary computational and hardware cost, provides a theoretical foundation and technical basis for the increasing demands of its practical applications. Considering its superior performance in degrees-of-freedom, spatial resolution, and computational complexity, research on coprime array signal processing has attracted much attention. This paper reviews recent research progress on coprime array signal processing, which has focused on both the Direction-of-Arrival (DOA) estimation and adaptive beamforming. From the perspective of coprime array DOA estimation, this paper summarizes two typical approaches, namely the coprime subarray decomposition-based approach and the virtual array signal processing-based approach. Moreover, recent work on low-complexity and super-resolution DOA estimation via compressive sensing and gridless techniques is also introduced. From the perspective of coprime array adaptive beamforming, the differences and relationships between DOA estimation and beamforming in the framework of coprime array signal processing are discussed, and an efficient, robust, and adaptive beamformer design tailored for the coprime array is introduced. Advantages and the future directions of coprime array signal processing are discussed, along with the theoretical basis and a technical reference for practical radar applications.
- Array signal processing /
- Coprime array /
- Direction-of-Arrival (DOA) estimation /
- Adaptive beamforming

HTML全文

图 1 互质阵列结构示意图

Figure 1. Illustration of the coprime array structure

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图 2 互质子阵列的MUSIC空间谱相位模糊示意图

Figure 2. Phase ambiguity of the pair of coprime subarray in the MUSIC spatial spectrum

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图 3 波达方向估计性能对比

Figure 3. Comparison of DOA estimation performance

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图 4 互质阵列及其对应的各种虚拟域阵列结构示意图

Figure 4. Illustration of the coprime array and its corresponding virtual array structures

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图 5 单个随机信号源情况下的波达方向估计性能对比

Figure 5. Comparison of DOA estimation performance under the single random source scenario

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图 6 算法复杂度性能对比

Figure 6. Comparison of algorithm complexity

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图 7 观测方向存在随机误差情况下的输出性能对比

Figure 7. Comparison of output SINR performance under the random signal look direction mismatch scenario

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