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Simulation Study of SVM-Based Approach in Extracting Parameters for Electromagnetic Detection of Buried Object

Simulation Study of SVM-Based Approach in Extracting Parameters for Electromagnetic Detection of Buried Object
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摘要 In this paper,a new method for extracting the parameters of buried object is proposed.The center position and dielectric properties of 2-D buried object are estimated by means of a regression technique based on support vector machine（SVM）.The proposed method,after a proper training procedure,is able to reconstruct the center position and dielectric properties of a buried object inside a given investigation domain.Numerical simulation results indicate that SVM-based approach shows higher accuracy than the back-propagation neural networks（BPNN） algorithm. In this paper,a new method for extracting the parameters of buried object is proposed.The center position and dielectric properties of 2-D buried object are estimated by means of a regression technique based on support vector machine（SVM）.The proposed method,after a proper training procedure,is able to reconstruct the center position and dielectric properties of a buried object inside a given investigation domain.Numerical simulation results indicate that SVM-based approach shows higher accuracy than the back-propagation neural networks（BPNN） algorithm.
作者 ZHANG Qinghe HE Siyuan ZHU Guoqiang
机构地区 School of Science School of Electronic Information
出处 《Wuhan University Journal of Natural Sciences》 CAS 2010年第6期510-515,共6页 武汉大学学报（自然科学英文版）
基金 Supported by the National Natural Science Foundation of China (50679037,60671040)
关键词 buried object detection inverse scattering support vector machine（SVM） buried object detection inverse scattering support vector machine（SVM）
分类号 TP212 [自动化与计算机技术—检测技术与自动化装置] V328 [航空宇航科学与技术—人机与环境工程]
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Wuhan University Journal of Natural Sciences
2010年 第6期

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