Short wave protocol signals recognition based on Swin-Transformer - Zhengyu ZHU; Pengfei CHEN; Zixuan WANG; Kexian GONG; Di WU; Zhongyong WANG (Tongxin xuebao)
Aiming at the problem that it is difficult to identify the protocol to which the signal belongs in the complex SW channel environment, a SW protocol signal recognition algorithm based on Swin-Transformer neural network model was proposed.Firstly, the gray-scale time-frequency map of the signal was obtained by using the time-frequency analysis method as the input of the neural network.Secondly, a neural network model based on swing transformer was designed to extract the features of the signal time-frequency map.Finally, the mapping relationship between the features and the protocol was established to realize the recognition of the signal protocol.The simulation results show that the recognition accuracy of the proposed algorithm is close to 100% in the Gaussian channel with SNR greater than -4 dB, which is higher than the existing algorithms.In addition, under the channel conditions of strong interference and multipath delay fading, the proposed algorithm still has a high SW protocol signals recognition rate.