Background removal from GPR data using Eigenvalues
Background removal from GPR data using Eigenvalues
复制标题
使用特征值从探地雷达数据中去除背景
DOI：
10.1109/icgpr.2010.5550079
复制
发表时间：
2010
期刊：
影响因子：
--
通讯作者：
W. Al
中科院分区：
文献类型：
--
作者：
Umar Shahbaz Khan;W. Al
地下扫描的探地雷达雷达图不仅有目标的反射，还有许多不需要的被称为杂波的物体的反射。此外，天线的直接波和耦合效应以及背景噪声也会对信号造成干扰。为了成功地提取目标特征，需要消除这些额外的噪声影响。虽然杂波不能完全从数据中去除，但背景去除技术在很大程度上抑制了杂波的影响。通常使用均值减法作为背景去除技术，但结果令人满意，还可以进一步改进。本文提出了一种基于特征值和均值减法的背景去除技术。该方法减小了杂波的影响，提高了输出精度。尽管该方法比传统的背景去除方法耗时稍长，但其输出消除了大部分杂波，因此自动探地雷达数据处理系统中的分割和分类阶段将更加高效，从而减少了近实时探地雷达数据处理的总体耗时。该方法已在多个不同的数据集上实现，结果表明，与现有的背景去除方法相比，该方法在背景去除方面有显著改善。
A GPR radargram of an underground scan has reflections not only from the target but many unwanted objects known as clutters. Additionally, the signal is corrupted by the direct wave and coupling effect of the antennas and background noise. In order to successfully extract the target signature, these extra noise effects need to be eliminated. Though the clutters cannot be totally removed from the data, background removal techniques suppress their effect to quite an extent. Usually mean subtraction is used as a background removal technique but the results are just satisfactory and further improvements can be made. In this paper an Eigenvalue based background removal technique in collaboration with mean subtraction is presented. This proposed method decreases the effect of clutters and the output is much more refined. Even though this method takes slightly more time than the traditional background removal methods, the output eliminates major portion of the clutter therefore the segmentation and classification stages in an automated GPR data processing system would be much more efficient hence reducing the overall time consumption for near real time GPR data processing. The method has been implemented on a number of different data sets and the results indicate that the proposed method gives significant improvement in background removal over the existing background removal methods.