Publication | Open Access
A Linear Prediction and Support Vector Regression-Based Debonding Detection Method Using Step-Frequency Ground Penetrating Radar
16
Citations
17
References
2018
Year
Highway PavementEngineeringDeterioration ModelingGeotechnical EngineeringData SciencePattern RecognitionBiostatisticsRadar Signal ProcessingPublic HealthAutomatic Target RecognitionSynthetic Aperture RadarStructural Health MonitoringInverse ProblemsRadar ApplicationSignal ProcessingLinear PredictionRadarCivil EngineeringStep-frequency GprRadar Image ProcessingGround-penetrating RadarBomb Damage Assessment
In the field of civil engineering, ground penetrating radar (GPR) is a highly efficient nondestructive testing tool for sustainable management of pavement infrastructures. GPR allows to evaluate the structure of the roadway over large distances (with contactless configurations) and to detect significant subsurface defects. This letter presents a new method to detect thin debondings within pavement structures with the step-frequency GPR. The proposed method enables us to carry out the detection with only a small number of frequency samples and A-scans. It is based on the linear prediction and support vector regression theories. Two experimental results show its effectiveness.
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