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基于核函数的雷达一维距离像目标识别 被引量：9

Range Profile Recogniton of Radar Target Based on the Kernel-Based Methods
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摘要 该文分析了基于核函数的三大模式识别方法(支持向量机、非线性主分量分析、非线性判别分析)的分类机理,并将其应用于雷达一维距离像目标识别中。用3种飞机实测雷达距离像数据样小进行识别研究,结果表明对于雷达目标距离像识别,支持向量机方法较其它两种方法更为有效,并对实验结果给出了合理的解释。 The classification mechanism of the kernel-based methods in pattern recognition, i.e. SVMs, nonPCA, and nonLDA, are analyzed in detail in this paper. The range profiles of radar target are recognized by the kernel-based methods. The results of the simulation on three radar target show that SVMs is more effective than nonPCA and nonLDA, and a sound explanation for the results is given too.
作者 孟继成 杨万麟
机构地区 电子科技大学电子工程学院
出处 《电子与信息学报》 EI CSCD 北大核心 2005年第3期462-466,共5页 Journal of Electronics & Information Technology
关键词 雷达目标识别 基于核函数的方法 支持向量机 非线性主分量分析 非线性判别分析 Radar target recognition, Kernel-based methods, Support vector machines, Nonlinear principal component analysis, Nonlinear discriminant analysis
分类号 TN957.7 [电子电信—信号与信息处理]
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参考文献11

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二级参考文献38

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共引文献85

同被引文献63

引证文献9

二级引证文献38

电子与信息学报
2005年 第3期

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