一种基于幅度和相位迭代重建的四维合成孔径雷达成像方法

任笑真; 杨汝良

doi:10.12000/JR15135

一种基于幅度和相位迭代重建的四维合成孔径雷达成像方法

DOI: 10.12000/JR15135 CSTR: 32380.14.JR15135

任笑真^,,
杨汝良

1.
(河南工业大学信息科学与工程学院郑州 450001)
2.
(中国科学院电子学研究所北京 100190)

基金项目:

国家自然科学基金(61201390),河南省教育厅科学技术研究重点项目(16A510004)和河南省高等学校青年骨干教师(2015GGJS038)

详细信息

作者简介:
任笑真(1984-),女,河南偃师人,2010年7月获得中国科学院电子学研究所通信与信息系统博士学位。现为河南工业大学副教授,硕士生导师,研究方位为合成孔径雷达成像和信号处理。E-mail:rxz235@163.com杨汝良(1943-),男,云南昆明人,1965年毕业于电子科技大学雷达系,英国ABERDEEN大学工程系高级访问学者。现为中国科学院电子学研究所航天微波遥感系统部研究员、博士生导师,从事星载、机载合成孔径雷达系统研究工作。

通讯作者:
任笑真rxz235@163.com

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- 被引次数: 0
出版历程
- 收稿日期: 2015-12-31
- 修回日期: 2016-01-24
- 网络出版日期: 2016-02-28

Four-dimensional SAR Imaging Algorithm Based on Iterative Reconstruction of Magnitude and Phase

Ren Xiaozhen^,,
Yang Ruliang

1.
(College of Information Science and Engineering, Henan University of Technology, Zhengzhou 450001, China)
2.
(The Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China)

Funds:

The National Natural Science Foundation of China (61201390), The Key Scientific Research Project in Universities of Henan Province (16A510004), The Plan for Young Backbone Teacher of Henan Province (2015GGJS038)

摘要

摘要: 4维合成孔径雷达获取的观测数据在基线-时间平面非均匀分布。若采用传统成像方法来获取目标散射体的高度-速率维像,则因强副瓣存在,成像效果不理想。当信号具有稀疏性时,压缩感知技术能够利用少量的信号投影值就可实现信号的准确或近似重构。然而标准的压缩感知成像方法是针对实数据进行处理,4维合成孔径雷达成像处理的数据为复数据。因此该文提出了一种基于幅度和相位迭代重建的4维合成孔径雷达成像方法。将4维合成孔径雷达高度-速率成像问题转化为目标复散射系数的幅度和相位联合重建问题,通过在成像过程中引入相位信息来改善成像质量。仿真结果验证了该算法的有效性。
- 合成孔径雷达 /
- 4维 /
- 复数成像 /
- 压缩感知
Abstract: Observation data obtained from the Four-Dimensional (4D) Synthetic Aperture Radar (SAR) system is sparse and non-uniform in the baseline-time plane. Hence, the imaging results acquired by traditional Fourier-based methods are limited by high side lobes. Compressive Sensing (CS) is a recently proposed technique that allows for the recovery of an unknown sparse signal with overwhelming probability from very limited samples. However, the standard CS framework has been developed for real-valued signals, and the imaging process for 4D synthetic aperture radar deals with complex-valued data. In this study, we propose a new 4D synthetic aperture radar imaging algorithm based on an iterative reconstruction of magnitude and phase, which transforms the height-velocity imaging problem of 4D synthetic aperture radar into a joint reconstruction problem of the magnitude and phase of the complex-valued scatter coefficient. Using the phase information in the algorithm, the image quality is improved. Simulation results confirm the effectiveness of the proposed method.
- Synthetic Aperture Radar (SAR) /
- Four-Dimensional (4D) /
- Complex-valued imaging /
- Compressive Sensing (CS)

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参考文献(14)

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