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Application of time-frequency peak filtering with minimum mean cross-entropy in ground penetrating radar signal denoising |
ZHENG Wei1( ), TIAN Ren-Fei1( ), GAO Yu-Han1, WU Bin2 |
1. College of Geophysics, Chengdu University of Technology, Chengdu 610059, China 2. Sichuan Geophysical Survey and Research Institute, Chengdu 610072, China |
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Abstract In practical detection operations using ground-penetrating radar (GPR), factors such as environmental noise and instrument errors frequently cause signals to be mixed with substantial noise, seriously reducing signal quality and the reliability of analytical results. To address this issue, this study proposed a time-frequency peak filtering method combined with minimum mean cross-entropy (TFPF-MMCE) for denoising GPR signals. This method combined time-frequency peak filtering with the cross-entropy function, enabling effective noise suppression and precise preservation of valid signals through precise optimization of the time-frequency representation, thereby significantly improving the quality of GPR signals. Numerical simulation and field GPR experiments validated that the TFPF-MMCE method exhibited a high noise removal capability and, thus, can effectively eliminate random noise while significantly improving signal clarity and reliability. Compared to traditional denoising methods, TFPF-MMCE shows significant advantages in denoising effectiveness and noise resistance stability, suggesting promising application potential and practical value in the field of GPR signal processing.
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Received: 18 July 2024
Published: 22 April 2025
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TFPF-MMCE algorithm flow chart
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Ground-penetrating radar geological model and corresponding forward modeling records
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The 46th ground-penetrating radar signal with added noise
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Comparison of denoising results between TFPF-PWV and TFPF-MMEC
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RMSE values and PSNR values under different signal-to-noise ratios
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去噪方法 | RMSE/10-4 | PSNR | TFPF-PWV | 5.37 | 65.38 | TFPF-MMCE | 3.24 | 69.78 | 双边滤波 | 3.74 | 68.55 | FIR滤波 | 7.51 | 62.48 | 均值滤波 | 3.83 | 68.34 | 小波变换 | 3.32 | 69.56 |
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Comparison of denoising effects among many methods
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Time-frequency peak filtering effect of ground-penetrating radar
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Time-frequency peak filtering effect after eliminating the direct wave
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[1] |
冯垣, 曾昭发, 刘四新, 等. 探地雷达信号处理[M]. 北京: 科学出版社, 2014.
|
[1] |
Feng Y, Zeng Z F, Liu S X, et al. Ground-penetrating radar signal processing[M]. Beijing: Science Press, 2014.
|
[2] |
杨林. 探地雷达铁路轨枕干扰特性分析[J]. 物探化探计算技术, 2024, 46(4):453-461.
|
[2] |
Yang L. Analysis of interference characteristics of ground penetrating radar railway sleepers[J]. Computing Techniques for Geophysical and Geochemical Exploration, 2024, 46(4):453-461.
|
[3] |
张斯薇, 吴荣新, 韩子傲, 等. 双边滤波在探地雷达数据去噪处理中的应用[J]. 物探与化探, 2021, 45(2):496-501.
|
[3] |
Zhang S W, Wu R X, Han Z A, et al. The application of bilateral filtering to denoise processing of ground penetrating radar data[J]. Geophysical and Geochemical Exploration, 2021, 45(2):496-501.
|
[4] |
张先武, 高云泽, 方广有. 带有低通滤波的广义S变换在探地雷达层位识别中的应用[J]. 地球物理学报, 2013, 56(1):309-316.
|
[4] |
Zhang X W, Gao Y Z, Fang G Y. Application of generalized S transform with lowpass filtering to layer recognition of Ground Penetrating Radar[J]. Chinese Journal of Geophysics, 2013, 56(1):309-316.
|
[5] |
黄敏, 朱德兵, 郭政学, 等. 连续小波变换在探地雷达信号分析中的应用研究[J]. 物探化探计算技术, 2012, 34(5):593-598,503.
|
[5] |
Huang M, Zhu D B, Guo Z X, et al. Research on the application of continuous wavelet transform in gpr signal analysis[J]. Computing Techniques for Geophysical and Geochemical Exploration, 2012, 34(5):593-598,503.
|
[6] |
Javadi M, Ghasemzadeh H. Wavelet analysis for ground penetrating radar applications:A case study[J]. Journal of Geophysics and Engineering, 2017, 14(5):1189-1202.
|
[7] |
Xu J C, Ren Q, Shen Z Z. Ground-penetrating radar time-frequency analysis method based on synchrosqueezing wavelet transformation[J]. Journal of Vibroengineering, 2016, 18:315-323.
|
[8] |
吴楠, 吴舰, 吴志坚. 探地雷达信号消噪中的时频谱分解重排算法[J]. 物探与化探, 2018, 42(1):220-224.
|
[8] |
Wu N, Wu J, Wu Z J. Research on denoising of ground penetrating radar signals using the time-frequency spectral decomposition reassignment algorithm[J]. Geophysical and Geochemical Exploration, 2018, 42(1):220-224.
|
[9] |
余世为, 牛刚, 覃晖, 等. 隧道超前地质预报溶洞探地雷达数据时频分析[J]. 工程勘察, 2023, 51(10):67-72.
|
[9] |
Yu S W, Niu G, Qin H, et al. Time and frequency analysis of GPR data for tunnel geological forecast of Karst caves[J]. Geotechnical Investigation & Surveying, 2023, 51(10):67-72.
|
[10] |
Li J, Zhao X L, Cheng H, et al. Data augmentation and denoising of magnetotelluric signals based on CS-ResNet[J]. Geophysics, 2025, 90(3):WA31-WA46.
|
[11] |
李月, 杨宝俊, 林红波, 等. 地震资料中随机强噪声压制——时频峰值滤波[J]. 中国科学:地球科学, 2013, 43(7):1123-1131.
|
[11] |
Li Y, Yang B J, Lin H B, et al. Suppression of strong random noise in seismic data by using time-frequency peak filtering[J]. Scientia Sinica:Terrae, 2013, 43(7):1123-1131.
|
[12] |
林红波, 马海涛, 李月, 等. 基于SW统计量的自适应时频峰值滤波压制地震勘探随机噪声研究[J]. 地球物理学报, 2015, 58(12):4559-4567.
|
[12] |
Lin H B, Ma H T, Li Y, et al. Elimination of seismic random noise based on the SW statistic adaptive TFPF[J]. Chinese Journal of Geophysics, 2015, 58(12):4559-4567.
|
[13] |
Liu Y, Peng Z, Wang Y, et al. Seismic noise attenuation by time-frequency peak filtering based on Born-Jordan distribution[J]. Journal of Seismic Exploration, 2018, 27(6):557-575.
|
[14] |
Liu N H, Yang Y, Li Z, et al. Seismic signal de-noising using time-frequency peak filtering based on empirical wavelet transform[J]. Acta Geophysica, 2020, 68(2):425-434.
|
[15] |
Boashash B, Mesbah M. Signal enhancement by time-frequency peak filtering[J]. IEEE Transactions on Signal Processing, 2004, 52(4):929-937.
|
[16] |
Loughlin P, Pitton J, Hannaford B. Approximating time-frequency density functions via optimal combinations of spectrograms[J]. IEEE Signal Processing Letters, 1994, 1(12):199-202.
|
[17] |
Groutage D. A fast algorithm for computing minimum cross-entropy positive time-frequency distributions[J]. IEEE Transactions on Signal Processing, 1997, 45(8):1954-1970.
|
[18] |
Shah S I, Loughlin P J, Chaparro L F, et al. Informative priors for minimum cross-entropy positive time-frequency distributions[J]. IEEE Signal Processing Letters, 1997, 4(6):176-177.
|
[19] |
Aviyente S, Williams W J. Minimum entropy time-frequency distributions[J]. IEEE Signal Processing Letters, 2005, 12(1):37-40.
|
[20] |
Moca V V, Bârzan H, Nagy-Dăbâcan A, et al. Time-frequency super-resolution with superlets[J]. Nature Communications, 2021, 12(1):337.
|
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