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 recognition.The successful application of Shearlet transform in image and seismic data shows its superiority for denoising process.When using the Shearlet transform to reduce the noise of the data, the choice of threshold has a great influence on the denoising effect.In 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 targets.The method is applied to process was proposed the simulation and field datasets, and the experimental results show that the method is effective.
