Research on Ground Penetrating Radar Target Identification Based on Support Vector Machines in Shallow Subsurface Application

ZHANG Chun-cheng; ZHOU Zheng-ou

您当前的位置：

首页 >

文章列表页 >

Research on Ground Penetrating Radar Target Identification Based on Support Vector Machines in Shallow Subsurface Application

更新时间：2025-07-16

- Research on Ground Penetrating Radar Target Identification Based on Support Vector Machines in Shallow Subsurface Application
- Acta Electronica Sinica Vol. 33, Issue 6, Pages: 1091-1094(2005)
- 作者机构：
  
  电子科技大学电子工程学院704教研室,四川,成都,610054
- 作者简介：
- 基金信息：
- DOI：
  CLC： TN955.1
- Published：2005
- 稿件说明：
移动端阅览
ZHANG Chun-cheng, ZHOU Zheng-ou. Research on Ground Penetrating Radar Target Identification Based on Support Vector Machines in Shallow Subsurface Application[J]. Acta Electronica Sinica, 2005, 33(6): 1091-1094.
DOI：

ZHANG Chun-cheng, ZHOU Zheng-ou. Research on Ground Penetrating Radar Target Identification Based on Support Vector Machines in Shallow Subsurface Application[J]. Acta Electronica Sinica, 2005, 33(6): 1091-1094. DOI：

摘要

对于探地雷达用于探测地雷情况下的目标识别

从实用性上说只需识别地雷或非地雷两类目标即可

而通常的支持向量机正是用于两类分类.本文结合浅地层探地雷达数据的特点

提出了一种基于支持向量机的浅地层探地雷达目标分类识别方法

并分析了时域

傅立叶谱

及离散小波变换三种特征数据用于所提方法时的效果.通过对实测数据进行处理

结果表明三种特征数据用于所提方法都能取得较好的效果.

Abstract

Ground penetrating radar(GPR) is an effective tool to detect mine.Ground penetrating radar target identification needs to distinguish mine and non-mine only

and support vector machines(SVM) can be used to two-class classification problem in practice.This paper analyzed the characteristic of shallow subsurface GPR data

proposed a method of GPR target identification based on support vector machines

and processed measurement data by using the proposed method in time sample

Fourier spectra

and discrete wavelet transform as feature data.The results of processing measurement data show this method is effective.

关键词

Keywords

references

Views

932

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Review on the Application of Metasurface-Based Impedance Matching Layer for Non-Destructive Testing Signal Enhancement

DABP: A Deep Learning Based Auto Focusing Back Projection Imaging Method for Ground Penetrating Radar

Construction of Dense Time-Varying Array with Constraint Embedded Based on ControlVAE

Suppression of Linear Interference Signal in GPR Profiling by Improved f-k Filtering Approach

A Novel Fast Imaging Technology of Microwave Array Based on Lens Imaging Principle

Related Author

LI Xiao-jing

ZHENG Wu-an

HAO Tong

LÜ Rong-qi

JIANG He-jun

SUI Hao

LEI Wen-tai

SUN Wen-li

Related Institution

School of Physics Science and Engineering, Tongji University

Center for Spatial Information Science and Sustainable Development Applications, Tongji University

College of Surveying and Geo-Informatics, Tongji University

School of Electronic Information, Central South University

Science and Technology on Near-Surface Detection Laboratory

⁰