航空兵器2024，Vol.31Issue(2)：17-31,15.DOI:10.12132/ISSN.1673-5048.2024.0065
电磁目标表征:知识-数据联合驱动新范式
A New Paradigm for Knowledge-Data Driven Electromagnetic Target Representation
摘要
Abstract
Electromagnetic target representation is a common fundamental problem in electromagnetic space situational awareness.Early target representation was based on expert empirical knowledge,which required de-signers to have strong professional background and prior knowledge,and is performed poorly in complex signal environments.Deep learning,which has been developed in recent years,provides a new way for signal repre-sentation in complex electromagnetic environments.It simulates the deep structure of the human brain to build a machine learning model to automatically represent and process target data in an end-to-end manner,and shows good performance in perception tasks such as electromagnetic target detection,classification,identification,pa-rameter estimation,and behavioral cognition.However,deep learning relies heavily on massive amounts of high-quality labelled data,and has certain limitations in the real electromagnetic environment.Incorporating know-ledge into intelligent systems has always been the research direction of artificial intelligence.Combining know-ledge and data for electromagnetic target representation will hopefully improve target perception accuracy and generalization ability,and is becoming a new direction in electromagnetic target representation.This paper re-views the development process of electromagnetic target representation techniques,and provide an outlook on the new paradigm of electromagnetic target perception driven by joint knowledge-data.关键词
目标表征/专家知识/深度学习/知识-数据联合驱动/知识图谱Key words
target representation/expert knowledge/deep learning/joint knowledge-data-driven/know-ledge graph分类
军事科技引用本文复制引用
杨淑媛,杨晨,冯志玺,潘求凯..电磁目标表征:知识-数据联合驱动新范式[J].航空兵器,2024,31(2):17-31,15.基金项目
国家自然科学基金项目(U22B2018 （）
62276205) （）
