吉林大学学报(工学版) ›› 2026, Vol. 56 ›› Issue (8): 2150-2161.doi: 10.13229/j.cnki.jdxbgxb.20250012
• 交通运输工程·土木工程 • 上一篇
夏子涵1(
),薛松涛1,2,3,谢丽宇1,3,4(
),刘江5,周雷军5
Zi-han XIA1(
),Song-tao XUE1,2,3,Li-yu XIE1,3,4(
),Jiang LIU5,Lei-jun ZHOU5
摘要:
针对现有的探地雷达(GPR)技术在多层钢筋密集场景下,仍面临分辨率不足、信号重叠以及信噪比降低等问题,提出了一种基于扩频与极化增益补偿的多层钢筋探测方法。该方法通过优化频谱扩展技术,有效克服了频率跳变和数据融合中信息丢失的问题。同时,利用金属的电磁反射特性与极化反转增益放大机制,增强了钢筋反射信号的强度,从而显著提升钢筋探测的能力。CST数值模拟结果表明,金属反射信号的极化偏转特性能够显著提高回波信号中钢筋反射的信噪比,极化匹配传输效率最大可提升约20 dB。此外,在gprMax中对频谱扩展前后的探地雷达数据进行了模拟计算与后处理分析。结果表明,本文所提出的探地雷达扩频技术能够有效提升距离分辨率,解决了窄距双层钢筋反射信号混淆问题,成功实现了其独立定位,最大误差仅为 5.25%。此外,本文还进行了多信噪比工况下的鲁棒性分析,进一步验证了该方法在复杂实际环境中的适用性和可靠性。
中图分类号:
| [1] | Xu X, Li J, Qiao X, et al. Fusion of multiple time‐domain GPR datasets of different center frequencies[J]. Near Surf Geophys, 2019,17: 141-150. |
| [2] | Zhao W, Yuan L, Forte E, et al. Multi-frequency GPR data fusion with genetic algorithms for archaeological prospection[J]. Remote Sens-Basel, 2021, 13: No.2804. |
| [3] | Zhao W, Lu G. A novel multifrequency GPR data fusion algorithm based on time-varying weighting strategy[J]. IEEE Geosci Remote S, 2021,19: 1-4. |
| [4] | Guan Z, Liu W. Multi-Frequency GPR data fusion through a joint sliding window and wavelet transform-weighting method for top-coal structure detection[J]. Applied Sciences, 2024,14: No.2721. |
| [5] | Bi W, Zhao Y, Shen R, et al. Multi-frequency GPR data fusion and its application in NDT[J]. Ndt & E Int, 2020,115: No.102289. |
| [6] | de Coster A, Lambot S. Fusion of multifrequency GPR data freed from antenna effects[J]. IEEE J-Stars, 2018,11: 664-674. |
| [7] | Annan A P. Electromagnetic principles of ground penetrating radar[J]. Ground Penetrating Radar: Theory and Applications,2009,1: 3-41. |
| [8] | Leucci G. Ground penetrating radar: the electromagnetic signal attenuation and maximum penetration depth[J]. Scholarly Research Exchange, 2008,2008: No. 926091. |
| [9] | Liu Y, Li K, Jia Y, et al. Wideband RCS reduction of a slot array antenna using polarization conversion metasurfaces[J]. IEEE T Antenn Propag, 2015,64:326-331. |
| [10] | Lambot S, Slob E C, van den Bosch I, et al. Modeling of ground-penetrating radar for accurate characterization of subsurface electric properties[J]. IEEE T Geosci Remote, 2004,42: 2555-2568. |
| [11] | 任仕召, 魏光辉, 潘晓东, 等. 典型雷达装备带内连续波辐射效应试验研究[J]. 强激光与粒子束, 2020,32(5):61-66. |
| Ren Shi-zhao, Wei Guang-hui, Pan Xiao-dong, et al. Experimental study on radiation effect of in-band continuous wave on typical radar equipment[J]. High Power Laser and Particle Beams, 2020, 32(5): 61-66. | |
| [12] | Hiebel M. Fundamentals of Vector Network Analysis[M]. Berlin: Rohde & Schwarz, 2007. |
| [13] | Zhang J, Ye S, Lin Y, et al. A modified model for quasi-monostatic ground penetrating radar[J]. IEEE Geosci Remote S, 2019,17:406-410. |
| [14] | Qureshi M A, Schmidt C H, Eibert T F. Efficient near-field far-field transformation for nonredundant sampling representation on arbitrary surfaces in near-field antenna measurements[J]. IEEE T Antenn Propag, 2012,61: 2025-2033. |
| [15] | Mourmeaux N, Tran A P, Lambot S. Soil permittivity and conductivity characterization by full-wave inversion of near-field GPR data[C]∥Proceedings of the 15th International Conference on Ground Penetrating Radar, Brussels, Belgium, 2014: 497-502. |
| [16] | Noon D A. Stepped-frequency radar design and signal processing enhances ground penetrating radar performance[D]. St. Lucia: Department of Electrical and Computer Engineering,The University of Queensland, 1996. |
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