基于随机调制超表面的差分关联成像方法研究

年毅恒; 周宁宁; 朱士涛; 张安学

doi:10.12000/JR20136

基于随机调制超表面的差分关联成像方法研究

DOI: 10.12000/JR20136

西安交通大学信息与通信工程学院多功能材料与结构教育部重点实验室西安 710049

基金项目: 国家自然科学基金(62071371)，超高速电路设计与电磁兼容教育部重点实验室资助(LHJJ/2020-04)，雷达信号处理国防科技重点实验室资助

详细信息

作者简介:
年毅恒(1995–)，男，安徽蚌埠人，硕士，现为西安交通大学信息与通信工程学院博士生，主要研究方向为微波关联成像、雷达信号处理。E-mail: nyhxjtu2019@stu.xjtu.edu.cn

周宁宁(1996–)，女，河南周口人，学士，现为西安交通大学信息与通信工程学硕士生，主要研究方向为基于OAM的关联成像算法、传输超表面产生OAM。E-mail: zhouning96@stu.xjtu.edu.cn

朱士涛(1980–)，男，河北沧州人，博士，现为西安交通大学信息与通信工程学院副研究员，硕士生导师，主要研究方向为新型雷达信号处理方法、人工智能成像算法、微波关联成像、超材料孔径天线及微波量子雷达。E-mail: shitaozhu@xjtu.edu.cn

张安学(1972–)，男，河南安阳人，博士，现为西安交通大学电磁与信息技术研究所所长，教授，博士生导师，主要研究方向为新型天线与分集技术、移动通信微波射频技术、智能雷达信号处理、多天线通信系统与阵列信号处理、微波测试理论与系统设计等。E-mail: anxuezhang@mail.xjtu.edu.cn

通讯作者:
朱士涛 shitaozhu@xjtu.edu.cn

责任主编：李廉林 Corresponding Editor: LI Lianlin
中图分类号: TN95
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出版历程
- 收稿日期: 2020-11-01
- 修回日期: 2021-01-11
- 网络出版日期: 2021-04-28

Differential Coincidence Imaging Based on a Randomly Modulated Metamaterial Surface

School of Information and Communication Engineering, Xi’an Jiaotong University, Key Laboratory of Multifunctional Materials and Structures, Ministry of Education, Xi’an 710049, China

Funds: The National Natural Science Foundation of China (62071371), The Key Laboratory of High-Speed Circuit Design and EMC Ministry of Education (LHJJ/2020-04), The National Key Lab of Radar Signal Processing

More Information

Corresponding author: ZHU Shitao, shitaozhu@xjtu.edu.cn

摘要

摘要: 基于超表面的关联成像系统解决了关联成像系统探测效率低的问题，但其探测模式数量不足导致了其有效成像点数受限。针对这个问题，该文以参考辐射场空间分布1阶统计特征为基础，建立了基于随机调制超表面的关联成像信号模型，分析了成像误差，并与差分关联成像(DCI)方法相结合，给出了具有鲁棒性的基于超表面的关联成像方法，该方法利用不同模式的差分形成了新的探测模式，降低了相关函数的副瓣干扰，从而提升了成像质量。同时，对一种特殊的差分关联成像方法—梯度关联成像(GCI)方法的成像分辨率进行了分析，该方法通过对超表面单元的特殊设计，可以在不获取图像的情况下，直接在成像过程中提取出目标方位向的边缘信息，可以有效提升关联成像系统对目标边缘的提取能力。最后，通过仿真实验验证了该文理论分析的正确性。
- 一阶关联 /
- 随机调制超表面 /
- 差分关联成像 /
- 梯度关联成像 /
- 边缘信息 /
- 成像分辨率
Abstract: The coincidence imaging system based on a metamaterial surface solves the problem of low detection efficiency. Nevertheless, the number of effective imaging points is limited owing to the lack of the detection mode. To solve this problem, based on the first-order statistical characteristics of a reference-radiation field, a correlation-imaging signal model based on a randomly-modulated metamaterial surface is established, and the imaging error is analyzed. This study presents a robust coincidence imaging called Differential Coincidence Imaging (DCI), which uses the differential of different modes to form a new detection mode. The DCI analysis proves that it can improve the imaging quality. At the same time, the resolution of a special DCI method called the Gradient Coincidence Imaging (GCI) method is analyzed, which effectively improves the ability of extracting a target edge. With the special design of a metasurface unit, the edge information of a target can be extracted directly in the imaging process without obtaining an image. Finally, the proposed methods are validated through simulation experiments.
- First-order correlation /
- Randomly modulated metamaterial surface /
- Differential Coincidence Imaging (DCI) /
- Gradient Coincidence Imaging (GCI) /
- Edge information /
- Imaging resolution

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图 1 线性阵列信号模型示意图

Figure 1. Linear array signal model

下载: 全尺寸图片幻灯片

图 2 差分关联成像相关函数

Figure 2. The correlation function in differential coincidence imaging

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图 3 传统与差分关联成像不同辐射样本的相关系数

Figure 3. The correlation coefficient of detection modes in coincidence imaging and Differential Coincidence Imaging (DCI)

下载: 全尺寸图片幻灯片

图 4 传统与梯度关联成像的对比

Figure 4. The comparion between coincidence imaging and Gradient Coincidence Imaging (GCI)

下载: 全尺寸图片幻灯片

图 5 传统关联成像与梯度关联成像对比

Figure 5. The comparion of imaging between coincidence imaging and Gradient Coincidence Imaging (GCI)

下载: 全尺寸图片幻灯片

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