全极化探地雷达多极化数据融合分析研究

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薛策文^{1, 3,},
冯晅^{1, 2, 3, 4,,},
李晓天^{1, 3,},
梁文婧^{1, 3},
周皓秋^{1, 3},
王颖^{1, 3}
1.吉林大学地球探测科学与技术学院长春 130026
2.地球信息探测仪器教育部重点实验室(吉林大学) 长春 130026
3.近地面探测技术重点实验室无锡 214035
4.吉林大学国家发展与安全研究所长春 130012
基金项目:国家重点研发计划(2018YFC1503705)，近地面探测技术重点实验室(6142414180911)，中央高校基础研究基金(20130061110061)，吉林省科技发展项目(20180101091JC)

详细信息

作者简介:薛策文(1996–)，男，吉林人，吉林大学硕士生，研究方向为全极化探地雷达数据融合，探地雷达数据处理。E-mail: xuecw18@mails.jlu.edu.cn
冯晅：冯　晅(1973–)，男，博士，教授，博士生导师，吉林大学地球探测科学与技术学院副院长。2002年获吉林大学博士学位；日本東北大学(Tohoku University)博士后、研究助手(2003–2006)；美国麻省理工学院(MIT)访问(2014–2016); IEEE Senior Member。教育部新世纪优秀人才，国土资源部国土资源科技人才。主要研究方向为全极化探地雷达地下探测理论和技术、非线性弹性地震学。E-mail: fengxuan@jlu.edu.cn
李晓天(1995–)，男，河南人，吉林大学硕士生，研究方向全极化探地雷达系统、探地雷达数据处理。E-mail: lixt@mails.jlu.edu.cn

通讯作者:冯晅 fengxuan@jlu.edu.cn

责任主编：雷文太 Corresponding Editor: LEI Wentai
中图分类号:P631

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出版历程

收稿日期:2020-07-21
修回日期:2020-09-27
网络出版日期:2020-10-12

Multi-polarization Data Fusion Analysis of Full-Polarimetric Ground Penetrating Radar

XUE Cewen^{1, 3,},
FENG Xuan^{1, 2, 3, 4,,},
LI Xiaotian^{1, 3,},
LIANG Wenjing^{1, 3},
ZHOU Haoqiu^{1, 3},
WANG Ying^{1, 3}
1. College of Geo-Exploration Science and Technology, Jilin University, Changchun 130026, China
2. Key Laboratory of Geophysical Exploration Equipment, Ministry of Education (Jilin University), Changchun 130026, China
3. Science and Technology on Near-Surface Detection Laboratory, Wuxi 214035, China
4. Institute of National Development and Security Studies, Jilin University, Changchun 130012, China
Funds:The National Key Research and Development Program of China (2018YFC1503705), The Science and Technology on Near-Surface Detection Laboratory (6142414180911), The Fundamental Research Funds for the Central Universities (20130061110061), The Technology Development Program of Jilin Province (20180101091JC)

More Information

Corresponding author:FENG Xuan, fengxuan@jlu.edu.cn

摘要
摘要:对于相同地下目标体，相比大部分传统单极化探地雷达，全极化探地雷达(FP-GPR)可以测得更全面的极化数据，称为VV, HH, VH。为了对地下目标体进行更全面精细的成像和识别, 数据融合技术被应用于FP-GPR将3种不同极化模式的极化信息结合起来。然而，目前全极化探地雷达数据融合常用的加权平均融合方法，它会掩盖全极化的优点，同时也无法同时适应不同的散射机制。因此，该文提出了基于主成分分析(PCA)，拉普拉斯金字塔(LP)以及多尺度小波变换(WT)的3种FP-GPR数据融合方法。为了检验几种数据融合方法的可靠性，该文在实验室分别测量了代表3种不同基本散射机制目标体的FP-GPR数据进行分析, 引入瞬时振幅为主、梯度为辅的方法将加权平均融合方法与3种方法进行比较。结果表明该研究所应用的3种数据融合方法效果均优于加权平均融合，并且3种方法可以分别适应不同散射机制的目标体，主成分分析融合可以更好的应用于未知散射机制目标体。最后，将主成分分析融合应用于实际冰裂缝数据成像，得到很好的融合效果，且优于加权平均融合方法。
关键词:全极化探地雷达/
数据融合/
主成分分析/
拉普拉斯金字塔/
小波变换/
目标体成像
Abstract:Full-Polarimetric Ground Penetrating Radar (FP-GPR), compared to traditional single-polarimetric GPR, can obtain more comprehensive polarization data (such as VV, HH, and VH) for the same target. To ensure a more comprehensive targets’ image identification, data fusion technology is applied to FP-GPR so as to combine the polarization information of three different polarization modes. However, weighted average fusion is usually employed in FP-GPR data fusion, since it masks the advantages of full polarization and is unable to simultaneously adapt to different target scattering mechanisms. Based on Principal Component Analysis (PCA), Laplacian Pyramid (LP), and multi-scale Wavelet Transform (WT), this research proposes three FP-GPR data fusion methods. To check the reliability of several data fusion methods, we obtained FP-GPR data representing three different target scattering mechanisms in the laboratory and, then, compared the weighted average fusion method with the other three methods using instantaneous amplitude and gradient. The result shows that the three methods were better than the weighted average fusion and that they can be adapted to different target scattering mechanisms. However, PCA was used to fuse the unknown target scattering mechanisms. Finally, PCA fusion is applied to actual ice fracture data imaging, as it produces a better fusion effect than that of weighted average fusion.
Key words:Full-Polarimetric Ground Penetrating Radar (FP-GPR)/
Data fusion/
Principal Component Analysis (PCA)/
Laplacian Pyramid (LP)/
Wavelet Transform (WT)/
Target imaging

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