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2024 Vol.40, Issue 4 Preview Page
A Rational Ground Model and Analytical Methods for Numerical Analysis of Ground-Penetrating Radar (GPR)

GPR 수치해석을 위한 지반 모형의 합리적인 모델링 기법 및 분석법 제안

Sang-Yun Lee1
,
Ki-Il Song2*
,
June-Ho Park3
,
Hee-Hwan Ryu4
,
Tae-Hyuk Kwon5
이 상연1
,
송 기일2*
,
박 준호3
,
류 희환4
,
권 태혁5
1Member, Ph. D. Student, Dept. of Civil Engineering, Inha Univ.
2Member, Prof., Dept. of Civil Engineering, Inha Univ.
3Member, Ph. D. Student, Dept. of Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology
4Member, Principal Researcher, Structural & Seismic Technology Group, KEPRI
5Member, Associate Prof., Dept. of Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology
1정회원, 인하대학교 토목공학과 박사과정
2정회원, 인하대학교 토목공학과 정교수
3정회원, 한국과학기술원, 건설 및 환경공학과 박사과정
4정회원, 한국전력연구원 기술기획처 기술전략실 선임연구원
5정회원, 한국과학기술원, 건설 및 환경공학과 부교수
*Corresponding Author
31 August 2024. pp. 49-60
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Abstract

Ground-penetrating radar (GPR) enables rapid data acquisition over extensive areas, but interpreting the obtained data requires specialized knowledge. Numerous studies have utilized numerical analysis methods to examine GPR signal characteristics under various conditions. To develop more realistic numerical models, the heterogeneous nature of the ground, which causes clutter, must be considered. Clutter refers to signals reflected by objects other than the target. The Peplinski material model and fractal techniques can simulate these heterogeneous characteristics, yet there is a shortage of research on the necessary input parameters. Moreover, methods for quantitatively evaluating the similarity between field and analytical data are not well established. In this study, we calculated the autocorrelation coefficient of field data and determined the correlation length using the autocorrelation function. The correlation length represented the temporal or spatial distance over which data exhibited similarity. By comparing the correlation length of field data with that of the numerical model incorporating fractal weights, we quantitatively evaluated a numerical model for heterogeneous ground. Consequently, the results of this study demonstrated a numerical modeling technique that reflected the clutter characteristics of the field through correlation length.

Keywords
Autocorrelation function
Correlation length
Finite-Difference Time-Domain(FDTD)
Fractal
Ground Penetrating Radar(GPR)

지표투과레이더(Ground Penetrating Radar, GPR)는 빠른 탐사 속도로 광범위한 지역의 정보를 획득할 수 있으나, 데이터 해석에는 전문적인 지식이 필요하다. 많은 연구에서 다양한 조건과 상황에서 GPR 신호 특성을 분석하기 위해 수치해석 기법을 도입해왔다. 보다 현실적인 수치 모델을 구성하기 위해서는 지반의 불균질한 특성을 고려해야 한다. 지반의 불균질한 특성으로 인해 클러터(Clutter)가 발생하며, 클러터는 송신된 신호가 목표가 아닌, 다른 물체에 의해 반사되어 수신되는 신호를 의미한다. Peplinski 재료 모델과 프랙탈 기법은 이러한 불균질한 특성을 모사할 수 있지만, 입력 매개변수에 대한 연구가 부족하다. 또한, 현장 데이터와 해석 데이터의 유사성을 정량적으로 평가할 수 있는 방법도 확립되지 않았다. 본 연구에서는 현장 데이터의 자기상관 계수를 계산하고 자기상관 함수를 통해 상관 거리를 산출하였다. 상관 거리는 데이터가 유사성을 보이는 시간적 혹은 공간적 거리를 의미한다. 현장 데이터의 상관 거리와 프랙탈 가중치를 적용한 해석 모델의 상관 거리를 비교하여 불균질 지반에 대한 수치해석 모델을 정량적으로 평가하였다. 본 연구를 통해 현장의 클러터 특성을 반영한 수치 모델링 기법을 제시하였다.

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Information
  • Publisher :The Korean Geotechnical Society
  • Publisher(Ko) :한국지반공학회
  • Journal Title :Journal of the Korean Geotechnical Society
  • Journal Title(Ko) :한국지반공학회 논문집
  • Volume : 40
  • No :4
  • Pages :49-60
  • Received Date : 2024-05-31
  • Revised Date : 2024-06-25
  • Accepted Date : 2024-06-25
  • DOI :https://doi.org/10.7843/kgs.2024.40.4.49
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