Noise suppressing and direct wave arrivals removal in GPR data based on Shearlet transform

Abstract

We present a new application of Shearlet transform (ShT) for ground penetrating radar (GPR) to remove the direct wave arrivals and suppress random noise. In fact, the reflecting waves from the underground targets and the direct wave arrivals are sometimes overlapped when the targets are buried shallowly, which influences the arrival-time detection and the target-position location. Random noise is also one of the influencing factors. In this paper, ShT is introduced to remove the direct wave arrivals and suppress random noise. The original GPR data is transformed to ShT domain by using multi-scale and multi-direction properties of ShT. The direct wave arrivals and the remaining GPR signal are effectively separated. While we eliminate the direct wave arrivals, the GPR signal is not damaged. In ShT domain, GPR data can be expressed sparsely. The GPR signal is described by big Shearlet coefficients, but random noise is described by small ones. So we can use the threshold method depending on different scales and directions in ShT domain to suppress random noise. The GPR signal's signal to noise ratio (SNR) is enhanced. The synthetic and field GPR data verify the effectiveness of direct wave arrivals removal and random noise suppression based on ShT.