For digital radio frequency memory(DRFM)to generate signals cannot be effectively distinguished from the source sig-nal,using synchro squeeze wavelet transform the radar signal of the time domain is converted to the time frequency diagram.Using deep learning powerful image recognition capabilities,the source signal and DRFM signal recognition based on deep learning are implemented.The problem that the echo signal cannot be effectively distinguished from the DRFM deception signal in the radar sig-nal processing is resolved.The problem that is difficult to recognize DRFM deceptive interference in radar interference recognition is resolved also.In order to verify the reliability of the deep learning process,the training results are verified and analyzed through the explanatory algorithm of neural networks.The accuracy of the neural network judgment has reached 96.33%,and the recogni-tion accuracy is good.
关键词
干扰识别/时频变换/梯度加权类激活映射/导向反向传播/深度学习
Key words
interference identification/time-frequency conversion/gradient-weighted class activation mapping(Grad-CAM)/guided-back propagation/deep learning
维普
万方数据