Wavefield Reconstruction Inversion Based on the Multi-Scale Cumulative Frequency Strategy for Ground-Penetrating Radar Data: Application to Urban Underground Pipeline
Open Access
- 30 April 2022
- journal article
- research article
- Published by MDPI AG in Remote Sensing
- Vol. 14 (9) , 2162
Abstract
High-precision detection of the underground pipelines is an indispensable part of the development and construction of cities. At present, the inversion technology for ground-penetrating radar (GPR) data is an effective means of realizing shallow-underground-space visualization in the field of geophysical exploration. However, the traditional full-waveform inversion (FWI) method usually faces the problems of strong nonlinearity of the objective function, high dependence on the initial model, and huge calculation cost. For improving the accuracy and efficiency of GPR data inversion, a wavefield reconstruction inversion (WRI) strategy is used for GPR data imaging to reduce the nonlinearity of the inversion problem and the dependence on the initial model. Then, the frequency weighting strategy and the multi-scale method are adopted to avoid the high-frequency component data dominating the optimization process and enhance the stability of inversion. In this paper, two numerical experiments of pipeline models with different materials and spacing or buried depths verified that the proposed method can effectively reconstruct the subsurface pipelines, and further performance of our algorithm on the field data verified the reliability of high-precision imaging of urban underground pipelines, which shows great potential of application in the field of high-precision detection of the urban underground pipelines.Keywords
Funding Information
- National Natural Science Foundation of China (42074161, 42104143, 2021JJ30806, 2021zzts0270)
- Natural Science Foundation of Hunan Province, China (42074161, 42104143, 2021JJ30806, 2021zzts0270)
- Fundamental Research Funds for the Central Universities of Central South University (42074161, 42104143, 2021JJ30806, 2021zzts0270)
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