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Method for Compensating Signal Attenuation Using Stepped-Frequency Ground Penetrating Radar

机译:步进频率探地雷达补偿信号衰减的方法

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摘要

Ground penetrating radar (GPR) is a subsurface remote sensor that allows the user to detect, classify, and identify the buried target and structures. The radar signals are rapidly attenuated as they propagate into the ground; therefore, attenuation compensation is necessary for the visualization of the buried targets from GPR data. In this work, we developed a novel attenuation compensation approach based on the recently developed stepped-frequency continuous wave (SFCW) GPR system, which is a frequency domain sampling system with improved performance in dynamic range, sensitivity, and anti-interference ability. Because the regularly used time-varying gain function for compensating the attenuation of impulse GPR data does not make full use of the advancement of the SFCW modulation, an alternative procedure is proposed herein. The new approach is based the SFCW mechanism, and aims at improving the visualization of deeper targets by compensating the SFCW GPR signal attenuation. We first present the attenuation mode of the SFCW GPR echo, from which an inverse attenuation function is derived to compensate the amplitude loss. For the field measurement where the theoretical inverse attenuation function is difficult to achieve, we introduced a pseudo time–frequency distribution for estimating the inverse attenuation function. A procedure for amplitude attenuation has also been developed. Testing with both synthetic and experimental data return a good reconstruction of the signal amplitude, subsequently improving the ability for visualizing and detecting deeper targets.
机译:探地雷达(GPR)是一种地下远程传感器,允许用户检测,分类和识别掩埋的目标和建筑物。雷达信号传播到地面时会迅速衰减。因此,衰减补偿对于根据GPR数据可视化掩埋目标是必要的。在这项工作中,我们基于最近开发的步进频率连续波(SFCW)GPR系统开发了一种新颖的衰减补偿方法,该系统是一种在动态范围,灵敏度和抗干扰能力方面有所改进的频域采样系统。因为用于补偿脉冲GPR数据的衰减的常规使用的时变增益函数没有充分利用SFCW调制的发展,所以在此提出了一种替代过程。新方法基于SFCW机制,旨在通过补偿SFCW GPR信号衰减来改善更深目标的可视化。我们首先介绍SFCW GPR回波的衰减模式,从该模式可以导出反衰减函数以补偿幅度损失。对于难以实现理论反衰减函数的现场测量,我们引入了伪时频分布来估计反衰减函数。还已经开发了用于振幅衰减的程序。使用合成数据和实验数据进行测试,可以很好地重建信号幅度,从而提高可视化和检测更深目标的能力。

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