电子科技大学学报2025，Vol.54Issue(2)：203-209,7.DOI:10.12178/1001-0548.2024001
基于高维特征域的低分辨雷达小微目标分类识别方法
Classification and recognition method of small and micro targets in low resolution radar based on high dimensional feature domains
摘要
Abstract
The classification of small and micro targets at low altitude is one of the difficult problems in radar field,which seriously effects the detection performance of radar and the effectiveness of system combat command.In order to accurately and quickly identify small and micro targets at low altitude such as rotors,fixed wings and vehicles,a classification and recognition method of small and micro targets of low-resolution radar based on high-dimensional feature domain is proposed in this paper.A series of time-frequency micro features and track macro features are extracted from the signal layer,and high-dimensional feature domain is obtained by internal product and power transformation of features.A multi-level target classification and recognition model is established by using learning tree network to realize the classification and marking of small and micro targets at low altitude.The results show that this method can classify small and micro objects accurately and quickly.关键词
小微目标/低分辨雷达/高维特征/分类识别/学习树网络Key words
micro-target/low-resolution radar/high-dimensional feature/classification recognition/learning tree network分类
电子信息工程引用本文复制引用
徐好,吴琳拥,周云,任浩浩..基于高维特征域的低分辨雷达小微目标分类识别方法[J].电子科技大学学报,2025,54(2):203-209,7.基金项目
国家自然科学基金(42027805) （42027805）
