Parameter Inversion by a Modified Reflected Signal Reconstruction Method for Thin-Layered Media

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

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

Parameter estimation of layered media is an important application of ground penetrating radar (GPR). However, in the case of thin-layer detection, the limitation of GPR vertical resolution can lead to overlapping reflected signals, which seriously deteriorates the detection results. To solve this problem, a modified reflected signal reconstruction method based on reflected signal reconstruction is proposed in this letter. First, a forward model of the GPR reflected signal is constructed using the generalized reflection coefficient definition. Then, the parameter inversion is transformed into an optimization problem. The residue cost function is defined as the error square between the model and the actual reflected signal, which is minimized by using genetic algorithm. Furthermore, the generalized reflection coefficient spectrum is feasible to estimate the parameters of each layer as the initial values of the parameters required by the algorithm, thus improving the accuracy and convergence speed of the algorithm. Numerical, experimental, and field tests demonstrate that the method has a high time resolution and antinoise capability in the inversion of layered media parameters.

Original languageEnglish
Pages (from-to)958-962
Number of pages5
JournalIEEE Antennas and Wireless Propagation Letters
Volume21
Issue number5
DOIs
Publication statusPublished - 1 May 2022

Keywords

  • Generalized reflection coefficient
  • genetic algorithm (GA)
  • ground penetrating radar (GPR)
  • thin-layered media

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