南京航空航天大学学报（英文版）2021，Vol.38Issue(4)：607-615,9.
一种基于压缩传感和改进机场残差网络的信号调制模式识别方法
A Signal Recognition Algorithm Based on Compressive Sensing and Improved Residual Network at Airport Terminal Area
摘要
Abstract
It is particular important to identify the pattern of communication signal quickly and accurately at the airport terminal area with the increasing number of radio equipments. A signal modulation pattern recognition method based on compressive sensing and improved residual network is proposed in this work. Firstly,the compressive sensing method is introduced in the signal preprocessing process to discard the redundant components for sampled signals. And the compressed measurement signals are taken as the input of the network. Furthermore,based on a scaled exponential linear units activation function,the residual unit and the residual network are constructed in this work to solve the problem of long training time and indistinguishable sample similar characteristics. Finally,the global residual is introduced into the training network to guarantee the convergence of the network. Simulation results show that the proposed method has higher recognition efficiency and accuracy compared with the state-of-the-art deep learning methods.关键词
压缩传感/深度学习/残差网络/调制识别Key words
compressed sensing/deep learning/residual network/modulation recognition分类
交通工程引用本文复制引用
沈志远,李佳,王倩倩,胡莹莹..一种基于压缩传感和改进机场残差网络的信号调制模式识别方法[J].南京航空航天大学学报（英文版）,2021,38(4):607-615,9.基金项目
This work was supported by the Na-tional Natural Science Foundation of China(No.71874081),Special Financial Grant from China Postdoctoral Science Foundation(No.2017T100366)and Open Fund of Hebei Province Key laboratory of Research on data analysis method under dynamic electro-magnetic spectrum situation. （No.71874081）
