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Notice of Violation of IEEE Publication Principles: Ground Penetrating Radar Signal Processing Based on Morphological Component Analysis

机译：违反IEEE公开原理的通知：基于形态分析的地面穿透雷达信号处理

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Notice of Violation of IEEE Publication Principles "Ground Penetrating Radar Signal Processing Based on Morphological Component Analysis" by J. Zhang, H. Zhang, Y. Li, F. Gao, X. Wu, and F. Zhu in the Proceedings of the 10th International Conference on Modelling, Identification and Control (ICMIC), July 2018, pp.1-6 After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE's Publication Principles. This paper copied portions of text from the paper cited below. The original text was copied without attribution (including appropriate references to the original author(s) and/or paper title) and without permission. "Clutter Removal in Ground-Penetrating Radar Images Using Morphological Component Analysis" by Eyyup Temlioglu and Isin Erer in IEEE Geoscience and Remote Sensing Letters, December 2016, pp.1802-1806
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.
机译：违反IEEE出版物原则的通知 “基于形态分析分析的地面穿透雷达信号处理” J. Zhang，H. Zhang，Y. Li，F. Gao，X. Wu，以及F.朱镕基在第10届国际建模，识别和控制会议（ICMIC），2018年7月，第1-1-6届（委员会）的课程仔细和考虑了对此的内容和作者的审查纸质由一项适当构成的专家委员会，本文已被发现违反了IEEE的出版原则。 本文从下面引用的文件中复制了文本的部分。未经归因（包括对原作者和/或文件标题）的适当参考，未经许可，已复制原始文本。 使用形态分析的地面穿透雷达图像中的杂波去除“
通过Eyup Temlioglu和Isin Erer 在IEEE地球科学和遥感信中，2016年12月，PP.1802-1806
地面穿透雷达（GPR）是最受欢迎的地下检测设备并具有各种应用。然而，当使用GPR来检测目标时，由于目标位于表面附近，因此杂波对目标检测的影响非常严重。特别是在某些复杂的环境中，目标可以完全被杂乱覆盖。因此，减少杂波是主要任务。奇异值分解（SVD），主成分分析（PCA）和独立分量分析（ICA）通常用于目标检测。本文采用了一种基于形态分析（MCA）的方法，提出了分解模型区分目标和杂波。最后，通过视觉模拟证明了这种方法优于去除杂波的其他方法。

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