通信学报2023，Vol.44Issue(11)：13-24,12.DOI:10.11959/j.issn.1000-436x.2023227
面向无线电数字孪生的多感知节点卷积融合身份识别算法
Multi-sensing node convolution fusion identity recognition algorithm for radio digital twin
摘要
Abstract
Electromagnetic space is an important link to empower and coordinate sea,land,air,space and network.Elec-tromagnetic target recognition provides important radio target identity information for the twin construction of electro-magnetic space,so that it can describe and depict the identity situation of electromagnetic targets in digital space.How-ever,a single sensing node is vulnerable to interference,and its recognition performance is limited.Wrong recognition results will provide radio digital twin with conflicting identity information.Therefore,based on the requirements of radio digital twin in electromagnetic space,a radio target recognition framework for radio digital twin was constructed and a multi-sensing node convolution neural network individual identity fusion recognition algorithm was proposed.Compared with the nearest single sensing node,the recognition performance is improved by 6.29%by deploying the multi-node recognition network in the actual scene,which provides more accurate individual identity information.关键词
卷积神经网络/无线电数字孪生/多感知节点/身份融合识别Key words
convolution neural network/radio digital twin/multi-sensing node/identity fusion recognition分类
信息技术与安全科学引用本文复制引用
魏国峰,丁国如,焦雨涛,徐以涛,郭道省,汤鹏..面向无线电数字孪生的多感知节点卷积融合身份识别算法[J].通信学报,2023,44(11):13-24,12.基金项目
国家自然科学基金资助项目(No.U20B2038,No.62231027,No.62171462,No.61931011,No.62101594) Foundation Item:The National Natural Science Foundation of China(No.U20B2038,No.62231027,No.62171462,No.61931011,No.62101594) （No.U20B2038,No.62231027,No.62171462,No.61931011,No.62101594）
