GPR data noise attenuation based on the Shearlet transform
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Graphical Abstract
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Abstract
When using ground penetrating radar(GPR)to detect the underground target distribution,valid signal in receiving data tend to be susceptible to noise and the interference of air-ground waves,which will affect the accuracy of target recognition and increase the difficulty of target recognitionThe successful application of Shearlet transform in image and seismic data shows its superiority for denoising processWhen using the Shearlet transform to reduce the noise of the data,the choice of threshold has a great influence on the denoising effectIn order to improve the denoising effect for radar data,a novel denosing method combining singular value decomposition(SVD)method for suppression of random noise to enhance the reflection signal caused by underground targetsThe method is applied to process was proposed the simulation and field datasets,and the experimental results show that the method is effective
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