现代电子技术2024，Vol.47Issue(15)：109-114,6.DOI:10.16652/j.issn.1004-373x.2024.15.018
基于SVM的小样本不均衡HRRP舰船目标分类方法
Small-sample imbalanced HRRP ship target classification method based on SVM
摘要
Abstract
In view of the small-sample imbalance in the classification of measured HRRP(high resolution range profile)military ships and civilian ships,a feature extraction method combining Relief algorithm and PCA(principal component analysis)algorithm is proposed,and the oversampling algorithm and error iterative weighting method are introduced to improve the SVM classifier.In this classification method,the original high-dimensional HRRP image is subjected to preprocessing and feature subspace weight,which enhances the separability of the main features,and the classification effect of the improved SVM classifier is improved significantly after iterative weighting.As a comparison,the classification effect of the adaptive enhanced SVM classifier is analyzed on the same measured HRRP ship target dataset.Experimental results show that the iteratively weighted Smote-SVM classification method with improved kernel space has better recognition effect and adaptability to the attitude sensitivity of HRRP.关键词
高分辨距离像/舰船目标分类/特征提取/支持向量机/改进SVM分类器/PCA算法Key words
HRRP/ship target classification/feature extraction/SVM/improved SVM classifier/PCA algorithm分类
信息技术与安全科学引用本文复制引用
查海刚,齐向阳,范怀涛..基于SVM的小样本不均衡HRRP舰船目标分类方法[J].现代电子技术,2024,47(15):109-114,6.基金项目
中科院空天院科学与颠覆性技术项目(E2Z216010F) （E2Z216010F）
