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首页> 外文期刊>Journal of Applied Geophysics >Detection of subsurface metallic utilities by means of a SAP technique: Comparing MUSIC- and SVM-based approaches
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Detection of subsurface metallic utilities by means of a SAP technique: Comparing MUSIC- and SVM-based approaches

机译：通过SAP技术检测地下金属公用设施：比较基于MUSIC和SVM的方法

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摘要

The identification of buried cables, pipes, conduits, and other cylindrical utilities is a very important task in civil engineering. In the last years, several methods have been proposed in the literature for tackling this problem. Most commonly employed approaches are based on the use of Ground Penetrating Radars, i.e., they extract the needed information about the unknown scenario starting from the electromagnetic field collected by a set of antennas. In the present paper, a statistical method, based on the use of smart antenna techniques, is used for the localization of a single buried object. In particular, two efficient algorithms for the estimation of the directions of arrival of the electromagnetic waves scattered by the targets, namely the MUltiple SIgnal Classification and the Support Vector Regression, are considered and their performances are compared.
机译：在土木工程中，识别埋入的电缆，管道，导管和其他圆柱形公用设施是一项非常重要的任务。近年来，文献中已经提出了几种解决该问题的方法。最常用的方法是基于探地雷达的，即，它们从一组天线收集的电磁场中提取有关未知场景的所需信息。在本文中，基于智能天线技术的统计方法被用于单个掩埋物体的定位。特别是，考虑了两个有效的算法来估计目标散射的电磁波的到达方向，即多重信号分类和支持向量回归，并比较了它们的性能。

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