希尔伯特-黄变换
探地雷达
计算机科学
熵(时间箭头)
噪音(视频)
人工智能
雷达
算法
信号(编程语言)
噪声测量
模式识别(心理学)
降噪
白噪声
物理
电信
图像(数学)
程序设计语言
量子力学
作者
Wei Xue,Xiangyang Dai,Jichao Zhu,Yan Luo,Yue Yang
标识
DOI:10.1109/lgrs.2019.2902123
摘要
Ensemble empirical mode decomposition (EEMD) is a noise-assisted analysis method, which can overcome the mode mixing problem in empirical mode decomposition (EMD). However, the choice of signal intrinsic mode functions (IMFs) still depends on subjective experience in most cases. In order to solve the problem, a noise suppression method based on EEMD and permutation entropy (PE) is proposed according to the characteristics of ground-penetrating radar (GPR) signal. In the proposed method, first EEMD is used to decompose the GPR signal into a series of IMFs, and the PE of each IMF is calculated; then, the global threshold obtained by the second-order difference of PE of all IMFs is used to distinguish between noise IMFs and target IMFs; finally, the signal is reconstructed with target IMFs to remove the noise. The experimental results for synthetic and practical GPR data show that the proposed method can effectively remove the noise in the GPR signal and improve the resolution of the target.
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