Automatic modulation recognition(AMR)of radiation source signals is a research focus in the field of cognitive ***,the AMR of radiation source signals at low SNRs still faces a great ***,the AMR method of radiation so...
详细信息
Automatic modulation recognition(AMR)of radiation source signals is a research focus in the field of cognitive ***,the AMR of radiation source signals at low SNRs still faces a great ***,the AMR method of radiation source signals based on two-dimensional data matrix and improved residual neural network is proposed in this ***,the time series of the radiation source signals are reconstructed into two-dimensional data matrix,which greatly simplifies the signal preprocessing ***,the depthwise convolution and large-size convolutional kernels based residual neural network(DLRNet)is proposed to improve the feature extraction capability of the AMR ***,the model performs feature extraction and classification on the two-dimensional data matrix to obtain the recognition vector that represents the signal modulation *** analysis and simulation results show that the AMR method based on two-dimensional data matrix and improved residual network can significantly improve the accuracy of the AMR *** recognition accuracy of the proposed method maintains a high level greater than 90% even at -14 dB SNR.
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