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

Abstract

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.