A Signal Recognition Algorithm Based on Compressive Sensing and Improved Residual Network at Airport Terminal Area; [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]

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. © 2021, Editorial Department of Transactions of NUAA. All right reserved.