Multi-frequency antenna ground penetrating radar data fusion method based on two-dimensional wavelet transform

Qiyue Ru; Feng Yang; Xu Qiao; Wenxing Shi; Fu Zhang; Haitao Zuo; Xinxin Huang

doi:10.1117/12.3034113

13 June 2024 Multi-frequency antenna ground penetrating radar data fusion method based on two-dimensional wavelet transform

Qiyue Ru, Feng Yang, Xu Qiao, Wenxing Shi, Fu Zhang, Haitao Zuo, Xinxin Huang

Author Affiliations +

Proceedings Volume 13180, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024); 131803Y (2024) https://doi.org/10.1117/12.3034113
Event: International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024), 2024, Guangzhou, China

Abstract

Ground Penetrating Radar (GPR), a prevalent urban road inspection technique, encounters operational limitations due to the shallow penetration of high-frequency antennas and the low resolution of low-frequency counterparts. To surmount these obstacles while catering to the requisites of both high data resolution and substantial detection depth, the present study introduces a novel data fusion methodology for multi-frequency GPR, leveraging the two-dimensional wavelet transform. Experimental validation was carried out using 300M and 400M radar frequencies, with metrics such as the average gradient, information entropy, spatial frequency and Laplacian operator gradient serving as the benchmarks for assessment. The empirical findings affirm the efficacy of the proposed approach in amalgamating the signal attributes of multi-frequency antennas, thereby markedly enhancing both the penetration depth and precision of GPR data.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Qiyue Ru, Feng Yang, Xu Qiao, Wenxing Shi, Fu Zhang, Haitao Zuo, and Xinxin Huang "Multi-frequency antenna ground penetrating radar data fusion method based on two-dimensional wavelet transform", Proc. SPIE 13180, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024), 131803Y (13 June 2024); https://doi.org/10.1117/12.3034113

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