# Suppression of Multiple Reflection Interference Signals in GPR Images Caused by Rebar Using VAE-GAN
## 1 Introduction  
In the inspection of tunnel linings, the presence of voids represents a common and serious structural defect. These voids not only compromise the load-bearing capacity of the structure but also pose a risk of further structural deterioration, potentially leading to severe damage [1, 2, 3]. Therefore, accurately identifying and assessing voids in tunnel linings is of critical importance. Ground Penetrating Radar (GPR) is a widely used non-destructive testing (NDT) technology that utilizes high-frequency electromagnetic waves to detect subsurface structures. A typical GPR system consists of a transmitting and a receiving antenna. The transmitting antenna emits electromagnetic pulses into the structure, and when these waves encounter interfaces between materials with different dielectric properties--such as air voids, concrete, or rebars--part of the wave is reflected back to the receiving antenna, while the remainder continues to propagate. The received signals are then processed to generate radar images, which provide valuable insights into the internal structure of the tunnel lining and its surrounding environment [4]. However, GPR performance is significantly affected by environmental conditions. The penetrationdepth, resolution, and signal attenuation are influenced by the dielectric properties of the materials, with high moisture content and heterogeneous structures often degrading detection accuracy. A particularly significant challenge in GPR-based void detection is the strong electromagnetic reflections caused by rebars in tunnel linings. These reflections create prominent hyperbolic clutter in GPR images, which can obscure signals from voids beneath the rebars, making detection highly challenging [5; 6]. To improve the accuracy of void detection and facilitate automated interpretation of GPR data, it is essential to develop effective techniques for suppressing rebar-induced interference. Enhancing interference mitigation methods will contribute significantly to improving the reliability of GPR-based inspections, making void detection in tunnel linings more precise and efficient [7; 8; 9]. The goal of rebar interference signal suppression is to minimize the interference of rebar signals on defect signals, allowing for clear identification of defect signals. Traditional identification methods for defective signals primarily rely on handcrafted filtering techniques or transform-based approaches, such as wavelet decomposition or Hyp-curvelet transform. [PERSON] et al. [10] proposed a method for detecting and suppressing rebar signals. They used Hyp-curvelet transform to project the GPR time-space 2D signals into the scale space. By combining the initial phase of the defect signals under the rebar as well as the time-frequency characteristics, they eliminated the rebar signal components in the scale space, achieving rebar signal suppression by transforming the data back to the time-space domain. [PERSON] et al. [11] introduced a method for clutter suppression that utilizes the curvelet transform. By combining coefficient distribution and prior information such as clutter direction, they used curvelet transform in the clutter, noise, and artifact removal process, reducing noise and clutter artifacts in the data and improving the readability of GPR data during the buried pipeline localization process. [PERSON] et al. [12] proposed a noise reduction approach that combines complete ensemble empirical mode decomposition with wavelet decomposition. This approach can remove effective information within the intrinsic mode function (IMF) components during the de-noising process. [PERSON] et al. [13] proposed a method based on iterative F-k migration and demigration, combined with a mask window and classic GPR data processing steps, to remove rebar clutter in concrete structures, validated by numerical simulations and field experiments. [PERSON] et al.