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基于域适应的辐射源个体识别研究综述

A Review of Specific Emitter Identification Based on Domain Adaptation
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摘要 辐射源个体识别技术在军事场景中发挥着越来越重要的作用,在实际环境中辐射源设备发射的信号经常会受到噪声等因素影响,导致信号特征分布发生变化。由于域适应方法能有效解决这一问题,为此对近几年基于域适应的辐射源个体识别技术的发展现状进行综述。首先,概述域适应方法及其分类,介绍不同场景下的域适应方法;其次,介绍域适应方法的相关原理及其在辐射源个体识别领域的应用;再次,收集现有可用于辐射源个体识别研究的公开数据集;最后,根据辐射源个体识别存在的问题提出未来的发展方向。 The individual identification technology of radiation sources is playing an increasingly important role in military scenarios.In actual environments,the signals emitted by radiation source equipment are often affected by factors such as noise,leading to changes in the distribu-tion of signal characteristics.Due to the effective solution of domain adaptation methods to this problem,this article reviews the current devel-opment status of domain adaptation based radiation source individual identification technology in recent years.Firstly,provide an overview of domain adaptation methods and their classification,and introduce domain adaptation methods for different scenarios;Then introduce the rele-vant principles of domain adaptation methods and their applications in the field of individual identification of radiation sources;Next,collect publicly available datasets that can be used for individual identification research of radiation sources;Finally,based on the existing problems in individual identification of radiation sources,future development directions are proposed.
作者 张涛涛 谢钧 乔平娟 ZHANG Taotao;XIE Jun;QIAO Pingjuan(College of Command and Control Engineering,Army Engineering University of the PLA,Nanjing 210001,China)
出处 《软件导刊》 2024年第6期205-213,共9页 Software Guide
关键词 辐射源个体识别 迁移学习 域适应 最大均值差异 对抗学习 specific emitter identification transfer learning domain adaptation maximum mean discrepancy adversarial learning
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