Layered Media Parameter Inversion Based on Common Middle Point Model and Pattern Search Method

Renjie Liu, Xiaopeng Yang, Tian Lan, Yixuan Li, Xiaodong Qu

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

Ground-penetrating radar (GPR) is an effective detection tool for multilayered structures such as road detection and underground exploration. However, traditional inversion algorithm in GPR cannot achieve layered media parameter inversion accurately due to neglect of multiple reflections and complicated refraction effect. To address this issue, an inversion algorithm for layered media parameters based on common middle point (CMP) model and pattern search (PS) method is proposed in this letter. The proposed method combines the wave propagation equation and Snell's law to build the cost functions in CMP model, and takes the layered media parameters as the optimization variables. Both numerical and experiment results indicate that inversion efficiency and accuracy can be improved. The novel inversion algorithm saves at least a quarter of time to control relative errors within 1% and 6% in simulation and laboratory experiment, respectively. The field test in asphalt highway shows its potential benefits in the field of multilayered structure.

Original languageEnglish
Article number4023605
JournalIEEE Geoscience and Remote Sensing Letters
Volume19
DOIs
Publication statusPublished - 2022

Keywords

  • Common middle point (CMP)
  • Ground penetrating radar (GPR)
  • Parameter inversion
  • Pattern search (PS)

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