Advanced signal processing method for ground penetrating radar feature detection and enhancement
Advanced signal processing method for ground penetrating radar feature detection and enhancement
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用于探地雷达特征检测和增强的先进信号处理方法
DOI：
10.1117/12.2046338
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发表时间：
2014
影响因子：
3.8
通讯作者：
Tian Xia
中科院分区：
文献类型：
--
作者：
Yu Zhang;A. Venkatachalam;D. Huston;Tian Xia
本文主要研究针对公路路面和桥面检测的空中耦合超宽带(UWB)探地雷达(GPR)系统的新的信号处理算法。探地雷达硬件由高压脉冲发生器、高速8GSPS实时数据采集单元和定制的现场可编程门阵列(FPGA)控制元件组成。与现有的大多数低测量速度的探地雷达系统相比，该系统可以在正常公路速度(60英里/小时)下进行测量，水平分辨率高达每厘米10次。由于地下介质的复杂性和不确定性，探地雷达信号处理既重要又具有挑战性。在该探地雷达系统中，提出了一种基于Curvelet变换、2D高通滤波和指数尺度的自适应探地雷达信号处理算法，以在保留和增强地下特征的同时消除噪声和杂波。首先，利用Curvelet变换去除环境噪声和系统噪声，同时保持B超图像的距离分辨率。然后，建立了圆柱形目标和杂波的数学模型。基于这些模型的二维(2D)滤波去除了杂波，并增强了B扫描图像中的双曲线特征。最后，采用指数标度法对地下材料中的信号衰减进行补偿，改善信号的特征。为了进行性能测试和验证，在实验室和现场配置中进行了钢筋检测实验和地下特征检查。
This paper focuses on new signal processing algorithms customized for an air coupled Ultra-Wideband (UWB) Ground Penetrating Radar (GPR) system targeting highway pavements and bridge deck inspections. The GPR hardware consists of a high-voltage pulse generator, a high speed 8 GSps real time data acquisition unit, and a customized field-programmable gate array (FPGA) control element. In comparison to most existing GPR system with low survey speeds, this system can survey at normal highway speed (60 mph) with a high horizontal resolution of up to 10 scans per centimeter. Due to the complexity and uncertainty of subsurface media, the GPR signal processing is important but challenging. In this GPR system, an adaptive GPR signal processing algorithm using Curvelet Transform, 2D high pass filtering and exponential scaling is proposed to alleviate noise and clutter while the subsurface features are preserved and enhanced. First, Curvelet Transform is used to remove the environmental and systematic noises while maintain the range resolution of the B-Scan image. Then, mathematical models for cylinder-shaped object and clutter are built. A two-dimension (2D) filter based on these models removes clutter and enhances the hyperbola feature in a B-Scan image. Finally, an exponential scaling method is applied to compensate the signal attenuation in subsurface materials and to improve the desired signal feature. For performance test and validation, rebar detection experiments and subsurface feature inspection in laboratory and field configurations are performed.