路东伟1,,
邢世其1,,,
杨潇2,,
李永祯1,,
王雪松1,
1.国防科技大学电子信息系统复杂电磁环境效应国家重点实验室 长沙 410073
2.国防科技大学电子科学系 长沙 410073
基金项目:国家自然科学基金(61971429, 61901499)
详细信息
作者简介:孙豆：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
路东伟(1992–)，男，博士研究生，主要研究方向为合成孔径雷达对抗和雷达目标识别。E-mail: bookwormldw@qq.com
邢世其(1984–)，男，副研究员，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
杨潇：杨 潇(1983–)，男，助教，主要研究方向为雷达信号处理和雷达目标识别。E-mail: 297414430@qq.com
李永祯(1977–)，男，研究员，博士生导师，主要研究方向为极化雷达与电子对抗。E-mail: e0061@sina.com
王雪松(1972–)，男，教授，博士生导师，主要研究方向为极化雷达、目标识别与电子对抗。E-mail: wxs1019@vip.sina.com
通讯作者:邢世其 xingshiqi_paper@163.com
责任主编：仇晓兰 Corresponding Editor: QIU Xiaolan中图分类号:TN95
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出版历程
收稿日期:2020-07-06
修回日期:2020-09-24
网络出版日期:2020-10-15
Full-polarization SAR Joint Multidimensional Reconstruction Based on Sparse Reconstruction
SUN Dou1,,LU Dongwei1,,
XING Shiqi1,,,
YANG Xiao2,,
LI Yongzhen1,,
WANG Xuesong1,
1. State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System, National University of Defense Technology, Changsha 410073, China
2. Department of Electronic Science, National University of Defense Technology, Changsha 410073, China
Funds:The National Natural Science Foundation of China (61971429, 61901499)
More Information
Corresponding author:XING Shiqi, xingshiqi_paper@163.com
摘要
摘要:各极化通道独立处理和三维分步成像会忽视数据之间的关联性，造成散射中心的失配以及极化散射矩阵获取的不准确。鉴于此，该文提出一种基于稀疏重构的全极化联合多维重建方法。该方法通过设置联合稀疏约束对所有极化通道及所有维度进行联合，将全极化多维重建建模为多通道联合稀疏重构问题。通过数据插值对模型简化后，结合三维快速傅里叶变换、共轭梯度法和牛顿迭代法给出一种高效的模型求解方法，可以同时得到极化散射矩阵和目标三维信息。该文方法保证了不同极化通道、不同维度的稀疏支撑集一致，且充分利用了数据之间的关联性带来的额外信息。基于仿真数据和电磁计算数据的实验结果表明，该方法的性能不受目标类型影响，具有一定的抗噪性，能有效地获取目标的多维重建结果，得到的三维成像结果分辨率高且极化散射矩阵估计精度高。
关键词:合成孔径雷达/
全极化/
稀疏重构/
三维成像/
联合重建
Abstract:Independent processing of each polarization channel and three-dimensional multistage imaging ignore the correlation between data, resulting in the mismatch between scattering centers and the inaccurate acquisition of polarization scattering matrices. To address these issues, a full-polarization Synthetic Aperture Radar (SAR) joint multidimensional reconstruction method based on sparse reconstruction is proposed in this study. In this method, all polarization channels and dimensions are integrated by setting the joint sparse constraints, and the full-polarization SAR joint multidimensional reconstruction is modeled as a multichannel joint sparse reconstruction problem. After the model is simplified by data interpolation, an efficient model-solving method is proposed by combining the three-dimensional fast Fourier transform, conjugate gradient method, and Newton iteration method, where the polarization scattering matrix and three-dimensional information of the target can be obtained at the same time. The proposed method ensures that the sparse support sets of different polarization channels and dimensions are consistent and utilizes the additional information generated by the correlation between data. On the basis of the simulation and electromagnetic calculation data, the experimental results indicate that the proposed method is tolerant of noise and immune to the types of targets. Moreover, the proposed method can effectively obtain the multidimensional reconstruction results of the target, where both the resolution of the imaging results and the estimation accuracy of the polarization scattering matrix are high.
Key words:Synthetic Aperture Radar (SAR)/
Full-polarimetric/
Sparse reconstruction/
Three-dimensional imaging/
Joint reconstruction
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