Underground object detection based on cross correlation and Hough transform

Jian Wang, Yi Su
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引用次数: 7

Abstract

GPR object detection is always a challenge in most practical applications. The hyperbola feature in B-Scan data is a very important feature for GPR object detection. In this paper, a novel method based on cross correlation between adjacent A-scans is proposed to detect reflection hyperbola. The method includes four steps. B-scan data is firstly preprocessed to suppress clutters. Then, the reflection hyperbola is extracted based on cross correlation. An approach of feedback is presented to fit the extracted hyperbola. At last, Hough transform is adopted to determine whether there is an object or not. The proposed method is tested by both simulated and field data.
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探地雷达目标检测在大多数实际应用中一直是一个挑战。b扫描数据中的双曲线特征是探地雷达探测目标的一个重要特征。本文提出了一种基于相邻a扫描互相关的反射双曲线检测方法。该方法包括四个步骤。首先对b扫描数据进行预处理,抑制杂波。然后,基于互相关提取反射双曲线;提出了一种反馈方法来拟合所提取的双曲线。最后采用Hough变换判断是否存在目标。通过模拟和现场数据对该方法进行了验证。
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