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A Novel Radar Target Recognition Algorithm Based on SVM

机译:基于SVM的雷达目标识别新算法。

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摘要

To solve the problems and defections of existing methods of Support Vector Machine (SVM) classification, an improved Gaussian kernel based on SVM is proposed and a improved SVM model selection scheme combining Leave-One-Out method with One-Validation method is presented in this paper, Based on the High Resolution Range Profile (HRRP) of three types of target, a preprocessing method is introduced, the novel classification algorithm for HRRP based on the improved SVM is applied. Finally, experimental results prove that the improved SVM classifier has better performance on target-aspect stability, training set-size stability and anti-noise ability than traditional SVM.
机译:为了解决现有的支持向量机(SVM)分类的问题和缺陷,提出了一种基于SVM的改进的高斯内核,并提出了一种改进的SVM模型选择方案,其中包含一个验证方法的休假方法纸张基于三种类型的目标的高分辨率范围曲线(HRRP),介绍了一种预处理方法,应用了基于改进的SVM的HRRP的新型分类算法。最后,实验结果证明,改进的SVM分级器具有比传统SVM的目标方面稳定性,训练设定尺寸稳定性和抗噪声能力更好。

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