A Brief Review of the Hyperbola Signature Recognition Techniques for Ground Penetrating Radar

doi:10.3969/j.issn.0372-2112.2019.06.025

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A Brief Review of the Hyperbola Signature Recognition Techniques for Ground Penetrating Radar

更新时间：2025-07-02

- A Brief Review of the Hyperbola Signature Recognition Techniques for Ground Penetrating Radar
- Acta Electronica Sinica Vol. 47, Issue 6, Pages: 1366-1372(2019)
- 作者机构：
  
  1. 同济大学空间信息科学及可持续发展应用中心,上海,200092
  2. 同济大学测绘与地理信息学院,上海,200092
  3. 同济大学空间信息科学及可持续发展应用中心,上海,200092
  4. 同济大学测绘与地理信息学院,上海,200092
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.0372-2112.2019.06.025
  CLC： TP391.4
- Published Online：25 June 2019，
  
  Published：2019
- 稿件说明：
移动端阅览
A Brief Review of the Hyperbola Signature Recognition Techniques for Ground Penetrating Radar[J]. Acta Electronica Sinica, 2019, 47(6): 1366-1372.
DOI：

A Brief Review of the Hyperbola Signature Recognition Techniques for Ground Penetrating Radar[J]. Acta Electronica Sinica, 2019, 47(6): 1366-1372. DOI： 10.3969/j.issn.0372-2112.2019.06.025.

摘要

探地雷达作为一种重要的无损探测技术，可以准确快速对浅层地表进行成像，以获取埋设目标的空间与几何信息.该文在分析探地雷达成像模型与目标识别基本思路的基础上，简述和归纳了七类探地雷达图像双曲线特征的检测方法，分别为基于双曲线性质、时域信号分析、数字图像分析、机器学习、数学模型、综合性方法以及深度学习方法，最后展望了深度学习在双曲线形态识别中的应用前景.

Abstract

Ground penetrating radar (GPR)

as an important non-destructive detection technology

can image the shallow subsurface accurately and quickly to obtain the spatial and geometric information of the buried targets.This paper describes and summarizes seven detection methods of hyperbolic signatures in GPR images

i.e.

based on hyperbolic properties

based on the time domain signal analysis

based on the digital image analysis

based on the machine learning

based on the mathematical model

based on the comprehensive and deep learning methods.Finally

we discuss the application potential of the deep learning method for the recognition of hyperbolic signatures.

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