曾涛1,2,3,,
陈新亮1,3,,,
丁泽刚1,2,,
范宇杰1,2,,
温育涵1,2,
1.北京理工大学信息与电子学院雷达技术研究所 北京 100081
2.嵌入式实时信息处理技术北京市重点实验室 北京 100081
3.北京理工大学重庆创新中心 重庆 401120
基金项目:国家重点研发计划(2017YFC0804700)，国家****基金(61625103)，国家自然科学基金重点项目(91738302, 91438203)
详细信息
作者简介:卫扬铠(1995–)，男，湖北人。北京理工大学信号与信息处理专业博士研究生，主要研究方向为合成孔径雷达信号处理。E-mail: yangkai.wei@bit.edu.cn
曾涛：曾 涛(1971–)，男，天津人。北京理工大学研究员、博士生导师，主要研究方向为雷达信息、信号处理与系统设计。E-mail: z.ding@bit.edu.cn
陈新亮(1984–)，男，湖北人。北京理工大学讲师，硕士生导师，主要研究方向为雷达信号检测与成像处理。E-mail: chenxinliang@bit.edu.cn
丁泽刚(1980–)，男，河南人。北京理工大学研究员、博士生导师，主要研究方向为新体制雷达成像机理、成像处理和图像信息提取。E-mail: z.ding@bit.edu.cn
范宇杰(1995–)，女，河北人。现北京理工大学信号处理专业硕士研究生，主要研究高精度分布式合成孔径雷达成像算法。E-mail: 18743052515@163.com
温育涵(1995–) ，男，北京人。北京理工大学信息与电子学院硕士研究生，主要研究方向为雷达信号处理及成像算法。E-mail: yuhan.wen@bit.edu.cn
通讯作者:陈新亮 chenxinliang@bit.edu.cn
中图分类号:TN958计量
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出版历程
收稿日期:2019-08-30
修回日期:2019-12-04
网络出版日期:2019-12-20
Parametric SAR Imaging for Typical Lines and Surfaces
WEI Yangkai1,2,,ZENG Tao1,2,3,,
CHEN Xinliang1,3,,,
DING Zegang1,2,,
FAN Yujie1,2,,
WEN Yuhan1,2,
1. Radar Research Lab, School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China
2. Beijing Key Laboratory of Embedded Real-Time Processing Technology, Beijing 100081, China
3. Beijing Institute of Technology Chongqing Innovation Center, Chongqing 401120, China
Funds:The National key R & D plan (2017YFC0804700), The National Outstanding Youth Fund (61625103), The National Natural Science Foundation of China (91738302, 91438203)
More Information
Corresponding author:CHEN Xinliang, chenxinliang@bit.edu.cn
摘要
摘要:在复杂场景(特别是城区场景)合成孔径雷达(SAR)遥感成像中，存在大量线、面目标，如城区中的道路和建筑物边缘等目标，这些线面目标微波散射信号方向性强。传统SAR从单一视角获取场景的散射信息，且传统成像算法均基于点目标模型，使得传统SAR图像中线面目标主要特征表现为一系列的强散射点，而非线散射特征和面散射特征，最终造成SAR图像中目标不连续，SAR图像解译困难。因此，该文通过建立典型线段、三角面元目标的参数化回波模型，对线面目标SAR成像机理进行了深入细致的研究；并基于提出的参数化模型对线面目标进行参数化成像，即首先基于贝叶斯理论和所提的参数化模型对典型的线面目标进行分类判决，随后采用再成像的方式获得有效表征线、面目标散射特征的SAR图像，为线、面目标SAR图像解译提供有效支撑。最后，数值仿真实验成功验证了所提算法的有效性和正确性。
关键词:线、面目标/
合成孔径雷达/
参数化模型/
参数化成像
Abstract:In the Synthetic Aperture Radar (SAR) remote sensing imagery of complicated scenes (especially urban scenes), there are a large number of lines and surfaces, such as roads in urban areas and the surfaces of buildings. These microwave-signal-scattering features have strong directivity. Traditional SAR acquires the scattering information of a scene from a single observation, and traditional imaging algorithms are based on the point target model, which makes the main features of the lines and surfaces in traditional SAR images appear as a series of strong scattering points rather than line-scattering and surface-scattering features. This outcome ultimately causes the target to be discontinuous in the SAR image, thus making the SAR image difficult to interpret. Therefore, in this study, we conducted an in-depth and meticulous investigation of the SAR imaging mechanism for lines and surfaces by establishing a parametric echo model of typical lines and triangular surfaces. Based on the proposed parametric model, we performed parametric imaging of these lines and surfaces. Based on our results, we propose a parametric imaging method, in which the typical lines and surfaces are classified and determined based on Bayesian theory and the proposed parametric model. Then, an SAR image can be obtained that effectively characterizes the scattering features of the line and surface targets by visual imaging, which effectively facilitates SAR image interpretation. The results of our numerical simulation experiments verify the validity of the proposed method.
Key words:Lines and surfaces/
Synthetic Aperture Radar (SAR)/
Parametric model/
Parametric imaging
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