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基于支持向量机的电磁逆散射方法
引用本文:王芳芳,张业荣.基于支持向量机的电磁逆散射方法[J].物理学报,2012,61(8):84101-084101.
作者姓名:王芳芳  张业荣
作者单位:南京邮电大学电子科学与工程学院,南京,210003
基金项目:国家自然科学基金(批准号: 61071022)和江苏省高等学校研究生科研创新计划(批准号: CXZZ11-0381)资助的课题.
摘    要:为解决电磁逆散射问题,提出了一种实时逆散射方法,该方法利用支持向量机(SVM)将逆散射问题转化为一个回归估计问题. 基于SVM的电磁逆散射方法成功地解决了逆散射问题中的非线性和不适定性.利用穿墙问题测试了该方法的可行性和有效性, 测试结果表明,不论是无噪声还是有噪声的情况,该方法都能很好地对墙后目标进行探测与定位.此外, 在穿墙环境下用SVM预测模型讨论了接收天线的采样位置数对预测结果的影响.最后对多源设置下的预测误差进行了分析和研究, 研究表明,相比于单源情况多源设置有利于对墙后目标的识别.

关 键 词:逆散射  支持向量机  穿墙问题  多源设置
收稿时间:2011-05-16

An electromagnetic inverse scattering approach based on support vector machine
Wang Fang-Fang,Zhang Ye-Rong.An electromagnetic inverse scattering approach based on support vector machine[J].Acta Physica Sinica,2012,61(8):84101-084101.
Authors:Wang Fang-Fang  Zhang Ye-Rong
Institution:School of Electronic Science and Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
Abstract:In order to solve electromagnetic inverse scattering problem, a real-time inverse scattering method is proposed. This technique converts the inverse scattering problem into a regressed one using support vector machine (SVM). Electromagnetic inverse scattering method based on the SVM deals with nonlinearity and ill-posedness inherent in the inverse scattering problem successfully. The feasibility and the validity are tested by making use of simulating through-wall problem, and the results demonstrate that this approach can detect and position the targets behind the wall, no matter whether there exists noise or not. In the through-wall scenario, the influence of the number of sampling positions of receiving antenna on the predicted results is discussed using the predicted model of SVM. In the end, the predicted errors are analyzed and investigated in the multiple source scenario. The results show that this kind of setting is helpful for target identification in through-wall problem.
Keywords:inverse scattering  support vector machine  through-wall problem  multiple sources setting
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