RETRACTED: Ground Penetrating Radar Signal Processing Based on Morphological Component Analysis (Retracted Article)

被引：0
|
作者：
Zhang, Jianhua [1 ,2 ]
Zhang, Haohao [1 ,2 ]
Li, Yang [1 ,2 ]
Gao, Feng [1 ,2 ]
Wu, Xueli [1 ,2 ]
Zhu, Feng [3 ]
机构：
[1] Hebei Univ Sci & Technol, Shijiazhuang 050018, Hebei, Peoples R China
[2] Hebei Prov Res Ctr Technol Proc Engn Automat, Shijiazhuang 050018, Hebei, Peoples R China
[3] CCCC FHDI ENGN CO LTD, Guangzhou, Peoples R China
来源：
PROCEEDINGS OF 2018 10TH INTERNATIONAL CONFERENCE ON MODELLING, IDENTIFICATION AND CONTROL (ICMIC) | 2018年
关键词：
signal processing; MatGPR; morphological component analysis (MCA); ground-penetrating radar (GPR); water conservancy projects; FABRIC DEFECT DETECTION; SPARSE; REPRESENTATIONS; TEXTURE; CARTOON;
D O I：
10.1109/ICMIC.2018.8529936
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Ground-penetrating radar (GPR) is one of the most popular underground detection devices and has a wide range of applications. However, when using GPR to detect targets, since targets are located near the surface, the influence of clutter on target detection is very serious. Especially in some complex environments, targets may be completely covered by clutter. Thus, clutter reduction is the primary task. Singular value decomposition (SVD), principal component analysis (PCA) and independent component analysis (ICA) are commonly used for target detection. In this paper, a method based on morphological component analysis (MCA) is adopted, and a decomposition model is proposed to distinguish between target and clutter. Finally, it is proved by visual simulation that this method is superior to other methods in removing clutter.
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页数：6
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