摘要
探地雷达技术已经广泛应用于城市道路及地下空间隐伏病害的快速精细探测,但受城市环境复杂干扰影响,探地雷达数据掺杂噪声与杂波,导致数据信噪比低,影响处理与识别精度。为提高探地雷达数据的信噪比,得到高质量的探测数据,本文在传统小波阈值去噪算法的基础上,提出了一种基于粒子群算法的改进小波阈值去噪算法。采用MATLAB、gprMax2D工具进行去噪仿真实验。实验结果表明,本文提出的去噪算法与传统的软、硬阈值去噪算法相比,信噪比分别提高了28.02%、6.97%,均方误差分别降低了71.86%、31.88%,具有更好的去噪效果。将本文提出的算法运用到实测探地雷达数据处理过程中,可以为城市道路及地下空间安全提供技术支撑。
The ground penetrating radar technology has been widely used in the rapid and precise detection of hidden diseases in urban roads and underground spaces.However,due to the complex interference of urban environment,the ground penetrating radar data is mixed with noise and clutter,resulting in low signal-to-noise ratio of data and affecting the processing and identification accuracy.In order to improve the signal-to-noise ratio of ground penetrating radar data and obtain high-quality detection data,this paper proposes an improved wavelet threshold denoising algorithm based on particle swarm optimization algorithm on the basis of the traditional wavelet threshold denoising algorithm.Through the use of MATLAB and gprMax2D tools to carry out the denoising simulation experiment.The experimental results show that compared with the traditional soft and hard threshold denoising algorithms,the signal-to-noise ratio is increased by 28.02%and 6.97%respectively,and the mean square error is reduced by 71.86%and 31.88%respectively,which has better denoising effect.Applying the algorithm proposed in this paper to the data processing process of ground penetrating radar can provide technical support for the safety of urban roads and underground space.
作者
齐善鲁
范宝德
张迪
Qi Shanlu;Fan Baode;Zhang Di(School of Computer and Control Engineering,Yantai University,Yantai 264005,China;State Key Laboratory of Coal Resources and Safe Mining,Beijing 100083,China)
出处
《电子测量技术》
北大核心
2023年第1期17-24,共8页
Electronic Measurement Technology
基金
山东省自然科学基金(ZR2019MF060)
山东省高等学校科技计划项目(J18KZ01)资助
关键词
探地雷达
小波阈值去噪
粒子群算法
信噪比
均方误差
ground penetrating radar
wavelet threshold denoising
particle swarm optimization
signal to noise ratio
mean square error
作者简介
齐善鲁,硕士研究生,主要研究方向为数据处理,数据可视化。E-mail:1556225479@qq.com;范宝德,博士,教授,主要研究方向为可视化计算、智能信息系统。E-mail:fanbaodeyt@163.com;张迪,硕士研究生,主要研究方向为探地雷达数据处理。E-mail:914028977@qq.com
