信息工程大学学报2023，Vol.24Issue(6)：641-648,8.DOI:10.3969/j.issn.1671-0673.2023.06.001
基于特征融合网络的特定短波信号体制识别算法
Specific Shortwave Signal System Recognition Algorithm Based on Feature Fusion Network
摘要
Abstract
Shortwave signal system identification plays a very important role in the field of non-coop-erative communication.However,due to the extensive use of new system signals and the increasingly complex electromagnetic environment of short-wave channels,the identifiication of short-wave signal systems is difficult.In this paper,a signal system recognition algorithm based on feature fusion net-work is proposed to realize the function of specific shortwave signal system recognition.It uses the correlation denoising coefficient and cepstrum coefficient of wavelet transform as features,and uses residual network and long short-term memory network for feature extraction and feature fusion respec-tively.By using this network under the condition of shortwave channel,the average recognition rate of 9 kinds of specific system signals with 0 dB signal-to-noise ratio reaches 95.9％.关键词
短波信号/体制识别/特征融合/深度学习Key words
shortwave signal/system identification/feature fusion/deep learning分类
信息技术与安全科学引用本文复制引用
孙鹏,李保国,鹿旭..基于特征融合网络的特定短波信号体制识别算法[J].信息工程大学学报,2023,24(6):641-648,8.
