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Signal-to-noise Ratio Enhancement in Multichannel GPR Data via the Karhunen-Lo′eve Transform

机译:通过Karhunen-Lo'eve变换,多通道GPR数据中的信噪比增强

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Ground penetrating radar (GPR) has been widely used in civil engineering,landmine detection and identifi-cation,unexploded ordnance,environmental engineering, and so forth. But GPR signals from shallowly buried objects tend to be obscured by the return from the air-soil interface. So how to get rid of the disturbing effect of this background signal has been always a troublesome problem in practical engineering. Based on the study to the characteristic of real-world GPR data,we find that the background has much strong correlations from trace to trace. So we propose to use KLT to process GPR signal. Simulative and practical experimental data examples are included to demonstrate the effectiveness of the method. Results indicate that KLT technique can really eliminate the strong GPR background mostly. The signal-to-noise ratio of the data processed by KLT technique can be enhanced greatly.
机译:地面穿透雷达(GPR)已广泛用于土木工程,地雷检测和识别,未爆发的军械,环境工程等。但是,来自浅埋的物体的GPR信号倾向于被空气土界面的返回遮挡。所以如何摆脱这种背景信号的令人不安的效果一直是实际工程中的麻烦问题。基于对现实世界GPR数据的特征的研究,我们发现背景与痕迹有关的强烈相关性。所以我们建议使用KLT来处理GPR信号。包括模拟和实际的实际实验数据示例以证明该方法的有效性。结果表明,KLT技术可以大多来消除强大的GPR背景。通过KLT技术处理的数据的信噪比可以大大提高。

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