Research on Denoising of Non-Contact GPR Data Based on Discrete Wavelet Analysis
The non-contact detection mode of GPR has been widely used in the field of railway subgrade detection.Compared with the traditional contact detection mode,the GPR has a safer detection environment and higher acquisition efficiency.However,since the radar antenna leaves the track surface and maintains a certain height space,the signal is more susceptible to noise,so the signal analysis process is often difficult due to noise interference.In order to improve signal quality,this study used discrete wavelet transform technology to denoise the non-contact GPR signal,which is of great significance.This study uses different wavelet bases for processing and explores in depth the application effects of wavelet denoising methods,and then selects the most suitable wavelet waveforms and transformation parameters for the Shuozhou-Huanghua Heavy-Duty Railway subgrade.In the actual data testing process,better noise suppression and high signal-to-noise ratio are achieved by selecting appropriate wavelet basis functions and reconstructing scale coefficients.Through quantization parameter evaluation,a good balance is achieved between filtering effect and information retention.The research results can provide new ideas for non-contact GPR railway subgrade detection data processing and image recognition.
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