Study on signal denoising of ground penetrating radar based on intelligent wavelet transform
Because radar wave is disturbed seriously by voices and clutters on the condition of complicated geological conditions, conventional filtering signal processing methods are difficult to meet the need for an accurate de-noising signal image processing. Combining the wavelet transformation theory and intelligent optimization algorithm, the intelligent reducing noise method of particle swarm optimization (PSO)-wavelet threshold was proposed, which has the ability of dealing with the problem of signal noise accurately and fast. Rational threshold of coefficients of wavelet at different levels was searched by using PSO algorithm in the global scope; the intelligent optimization process of reducing the noise of ground penetrating radar signal was founded. Through the engineering practice of ground penetrating radar using in the advanced prediction of tunnel geological hazards, the result shows that the interference factors in the signals can be removed quickly on the basis of the de-noising method of intelligence wavelet transform. It paves a new way for realizing the fast and exact prediction of tunnel geological hazards.
Geohazard Forecast Ground Penetrating Radar Wavelet Denoising Intelligent Optimization
Guoqing Chen Guoshao Su Zhanfeng Fan Zhiheng Lin Zhifa Zeng
State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Te College of Architecture and Civil Engineering, Guangxi University, Nanning 530004, China State Key Laboratory of eohazard Prevention and Geoenvironment Protection, Chengdu University of Tec College of Architecture and Civil Engineering, Guangxi University,Nanning 530004, China
国际会议
成都
英文
583-586
2010-06-14（万方平台首次上网日期，不代表论文的发表时间）