基于特征增强的非均匀采样SAR三维稀疏成像

doi:10.12305/j.issn.1001-506X.2021.04.06

系统工程与电子技术 ›› 2021, Vol. 43 ›› Issue (4): 901-910.doi: 10.12305/j.issn.1001-506X.2021.04.06

基于特征增强的非均匀采样SAR三维稀疏成像

孙豆¹(), 邢世其^1,*(), 高海峰²(), 庞礴¹(), 李永祯¹(), 王雪松¹()

1. 国防科技大学电子科学学院电子信息系统复杂电磁环境效应国家重点实验室, 湖南长沙 410073
2. 陕西省地质调查院, 陕西西安 710054

收稿日期:2020-07-10 出版日期:2021-03-25 发布日期:2021-03-31
通讯作者: 邢世其 E-mail:sundou14@nudt.edu.cn;xingshiqi_paper@163.com;117968769@qq.com;pangbo84826@126.com;e0061@sina.com;wxs1019@vip.sina.com
作者简介:孙豆(1992-), 女, 博士研究生, 主要研究方向为极化雷达成像和雷达信号处理。E-mail: sundou14@nudt.edu.cn|邢世其(1984-), 男, 副研究员, 博士, 主要研究方向为极化雷达成像、雷达信号处理以及合成孔径雷达对抗。E-mail: xingshiqi_paper@163.com|高海峰(1986-), 男, 工程师, 硕士, 主要研究方向为遥感信号处理、干涉合成孔径雷达。E-mail: 117968769@qq.com|庞礴(1984-), 男, 讲师, 博士，主要研究方向为极化雷达成像、雷达信号处理。E-mail: pangbo84826@126.com|李永祯(1976-), 男, 研究员, 博士，主要研究方向为极化雷达信号处理、雷达电子对抗。E-mail: e0061@sina.com|王雪松(1972-), 男, 教授, 博士研究生导师, 博士，主要研究方向为极化信息处理、雷达目标识别。E-mail: wxs1019@vip.sina.com
基金资助:
国家自然科学基金(61971429);国家自然科学基金(61901499)

3D sparse imaging for non-uniformly sampled SAR based on feature enhancement

Dou SUN¹(), Shiqi XING^1,*(), Haifeng GAO²(), Bo PANG¹(), Yongzhen LI¹(), Xuesong WANG¹()

1. State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System, College of Electronic Science, National University of Defense Technology, Changsha 410073, China
2. Shaanxi Provincial Geological Survey Institute, Xi'an 710054, China

Received:2020-07-10 Online:2021-03-25 Published:2021-03-31
Contact: Shiqi XING E-mail:sundou14@nudt.edu.cn;xingshiqi_paper@163.com;117968769@qq.com;pangbo84826@126.com;e0061@sina.com;wxs1019@vip.sina.com

摘要/Abstract

摘要：

对于非均匀采样数据, 现有三维稀疏成像方法中的数据局部插值会带来误差, 且得到的分布式目标成像结果与其连续散射的本质不符。针对这些问题, 首先将成像问题直接建模为三维空间中联合的稀疏重构问题, 并通过选取候选散射中心进行字典降维; 然后, 在降维后的模型中增加三维特征增强约束项, 建立三维空间中相邻散射中心之间的联系; 最后, 结合高斯迭代法以及优化的信号处理技巧, 提出了一种高效的模型求解算法。实验结果表明, 相比于其他成像方法, 本文方法对旁瓣的抑制能力强, 成像结果分辨率高、精度高, 且保证了分布式目标成像结果的连续性。

关键词: 合成孔径雷达, 非均匀采样, 三维成像, 稀疏重建, 特征增强

Abstract:

For non-uniform sampling data, the local data interpolation in the existing three-dimensional (3D) sparse imaging methods will bring errors, and the imaging result of distributed targets is poor. To solve these problems, firstly, the imaging problem is directly modeled as a joint sparse reconstruction problem in 3D space, and the dictionary reduction is carried out by selecting the candidate scattering centers; secondly, the 3D feature enhancement constraints are added to the reduced model to establish the relationship between adjacent scattering centers in 3D space; finally, an efficient model solving algorithm is proposed by combining the Gaussian iterative method and the optimized signal processing scheme. The experimental results show that, compared with other imaging methods, the proposed method has a strong ability to suppress side lobe, whose imaging results are with high resolution and high precision, and performs well on distributed targets.

Key words: synthetic aperture radar, non-uniform sampling, three-dimensional (3D) imaging, sparse reconstruction, feature enhancement

中图分类号:

TN958.97

孙豆, 邢世其, 高海峰, 庞礴, 李永祯, 王雪松. 基于特征增强的非均匀采样SAR三维稀疏成像[J]. 系统工程与电子技术, 2021, 43(4): 901-910.

Dou SUN, Shiqi XING, Haifeng GAO, Bo PANG, Yongzhen LI, Xuesong WANG. 3D sparse imaging for non-uniformly sampled SAR based on feature enhancement[J]. Systems Engineering and Electronics, 2021, 43(4): 901-910.

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方法	3D-NUFFT	Austin	本文
时间/s	0.72	1.07	1.68

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基于特征增强的非均匀采样SAR三维稀疏成像

3D sparse imaging for non-uniformly sampled SAR based on feature enhancement

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