基于变换域稀疏压缩感知的艇载稀疏阵列天线雷达实孔径成像

李烈辰; 李道京; 黄平平

doi:10.12000/JR14159

基于变换域稀疏压缩感知的艇载稀疏阵列天线雷达实孔径成像

DOI: 10.12000/JR14159

1.
(中国科学院电子学研究所微波成像技术重点实验室北京 100190)
2.
(中国科学院大学北京 100049)
3.
(内蒙古工业大学雷达技术研究所呼和浩特 010051)

基金项目:

国家自然科学基金(61271422, 61201433)

详细信息

作者简介:
李烈辰(1988-),男,浙江杭州人,2010年于中国农业大学获得工学学士学位,现为中国科学院电子学研究所博士研究生,研究方向为基于阵列天线的高分辨率雷达成像技术。E-mail:chrislee365@hotmail.com李道京(1964-),男,陕西西安人,研究员,博士生导师,分别于1986年和1991年在南京理工大学获得工学学士和工学硕士学位,2003年于西北工业大学获得工学博士学位,2003年至2006年在中国科学院电子学研究所做博士后研究,主要研究方向为雷达系统和雷达信号处理。E-mail:lidj@mail.ie.ac.cn黄平平(1978-),男,山东海阳人,博士,副教授,2003年于山东理工大学获得工学学士学位,2007年于内蒙古工业大学获得工学硕士学位,2010年获中国科学院电子学研究所博士学位,现任内蒙古工业大学雷达技术研究所所长。主要研究方向为合成孔径雷达信号处理和微波遥感应用。E-mail:cimhwangpp@163.com

通讯作者:
李烈辰chrislee365@hotmail.com

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出版历程
- 收稿日期: 2014-12-24
- 修回日期: 2015-04-28
- 网络出版日期: 2016-02-28

Airship Sparse Array Antenna Radar Real Aperture Imaging Based on Compressed Sensing and Sparsity in Transform Domain

1.
(Science and Technology on Microwave Imaging Laboratory, Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China)
2.
(University of Chinese Academy of Sciences, Beijing 100049, China)
3.
(Radar Research Institute, Inner Mongolia University of Technology, Hohhot 010051, China)

Funds:

The National Natural Science Foundation of China (61271422, 61201433)

摘要

摘要: 该文针对飞艇平台,设计了基于组合巴克码的共形稀疏阵列,并对稀疏阵列的探测性能进行了分析。利用飞艇悬停的特点,可对前后不同时刻脉冲的实孔径成像结果进行干涉处理,去除散射单元的随机初相位,使图像在变换域稀疏。引入压缩感知方法,建立回波与变换域系数的关系,完成对地成像,可获得接近满阵阵列成效的图像质量。仿真数据处理结果验证了该方法的有效性。
- 压缩感知(CS) /
- 变换域稀疏 /
- 共形稀疏阵列 /
- 实孔径成像
Abstract: A conformal sparse array based on combined Barker code is designed for airship platform. The performance of the designed array such as signal-to-noise ratio is analyzed. Using the hovering characteristics of the airship, interferometry operation can be applied on the real aperture imaging results of two pulses, which can eliminate the random backscatter phase and make the image sparse in the transform domain. Building the relationship between echo and transform coefficients, the Compressed Sensing (CS) theory can be introduced to solve the formula and achieving imaging. The image quality of the proposed method can reach the image formed by the full array imaging. The simulation results show the effectiveness of the proposed method.
- Compressed Sensing (CS) /
- Sparsity in the transform domain /
- Conformal sparse array /
- Real aperture imaging

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参考文献(20)

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