Random noise de-noising and direct wave eliminating in ground penetrating radar signal using SVD method

C. Song, Q. Lu, Cai Liu, Y. Gao
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引用次数: 9

Abstract

In this paper, we present a method using singular value decomposition (SVD) which aims at eliminating the random noise and direct wave from ground penetrating radar (GPR) signal. To demonstrate the validity and high efficiency of the eliminating random noise method using SVD, we first tested our proposed method with noisy synthetic data and field data. Then we carried out de-noising process using wavelet threshold de-noising method with the same data. After this, in order to demonstrate that SVD method can eliminate direct wave effectively, we tested our proposed method with synthetic data and field data. Next, we carried out direct wave eliminating process using mean trace deletion with the same data. We found that by choosing appropriate singular values after SVD with respect to GPR data, SVD method can eliminate the random noise and direct wave in the GPR data validly and efficiently to improve the resolution of the GPR profile.
利用奇异值分解方法对探地雷达信号进行随机噪声去噪和直接波去噪
本文提出了一种利用奇异值分解(SVD)去除探地雷达信号中的随机噪声和直接波的方法。为了验证奇异值分解消除随机噪声方法的有效性和高效性,我们首先用有噪声的合成数据和现场数据对我们提出的方法进行了测试。然后对相同的数据采用小波阈值去噪方法进行去噪处理。之后,为了证明奇异值分解方法可以有效地消除直波,我们用合成数据和现场数据对所提出的方法进行了测试。其次,采用相同数据的平均迹线删除法进行直接消波处理。通过对探地雷达数据进行奇异值分解后选择合适的奇异值,可以有效地消除探地雷达数据中的随机噪声和直波,提高探地雷达剖面的分辨率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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