电子学报2025，Vol.53Issue(7)：2401-2417,17.DOI:10.12263/DZXB.20240860
基于关键部件特征关联的ISAR空间目标多角度识别方法
Multi-Angle ISAR Recognition Method for Space Targets Based on Feature Correlation of Key Components
摘要
Abstract
The geosynchronous space situational awareness program(GSSAP)satellite of the USA has repeatedly or-bited and detected our satellites in recent years,which is a great threat.For this kind of orbiting maneuvering spacecraft,its continuous spin,spin axis change and orbiting motion vector constitute a three-dimensional rotation,and the scattering char-acteristics between adjacent inverse synthetic aperture radar(ISAR)image frames are greatly different,making it difficult to recognize it.To this end,this paper proposes a multi-angle ISAR recognition model for space targets based on feature corre-lation of key components.A contrast learning module based on self-supervised learning strategy is constructed to reduce the impact of parameter changes in imaging and target attitude on image recognition.A key component feature correlation mod-ule is constructed to mine local correlation information between key components of the images using graph information rea-soning methods.Finally,a complex-valued transformer layer extracts global contextual features between image blocks and achieves effective expression of the target through feature fusion.Experimental results based on real radar data show that the proposed method can significantly improve the effect of multi-angle recognition.Under the same recognition condition of data volume,the recognition rate is increased by 5.58%compared with the existing recognition method,verifying the per-formance of multi-angle recognition.关键词
逆合成孔径雷达/空间目标/机动目标/复数域网络/目标识别Key words
inverse synthetic aperture radar/space target/maneuvering target/complex-valued network/target rec-ognition分类
信息技术与安全科学引用本文复制引用
袁浩轩,张云,黄艳堃,田金,孔维民,陈李田..基于关键部件特征关联的ISAR空间目标多角度识别方法[J].电子学报,2025,53(7):2401-2417,17.基金项目
中国博士后科学基金(No.2023M734272) （No.2023M734272）
国家自然科学基金(No.62371170,No.62201612) China Postdoctoral Science Foundation(No.2023M734272) （No.62371170,No.62201612）
National Natural Science Founda-tion of China(No.62371170,No.62201612) （No.62371170,No.62201612）
