基于改进1DCNN+TCN的雷达辐射源快速识别方法

为了解决传统雷达辐射源识别方式识别速度慢、在低信噪比时很难准确识别等问题,结合深度学习提出了一种基于改进一维卷积神经网络(one-dimensional convolutional neural network,1DCNN)和时间卷积网络(temporal convolutional network,TCN)的雷达辐射...

Rapid recognition method of radar emitter based on improved 1DCNN+TCN

In order to solve the problems of low recognition speed and that it is difficult to accurately identify radar emitter in low signal-to-noise ratios(SNRs),a fast radar emitter recognition model based on improved one-dimensional convolution neural network(1DCNN)and temporal convolution network(TCN)is proposed.In this paper,a batch normalization layer is added to the 1DCNN,and the attention mechanism is added before the full connection layer;at the same time,it is improved on the basis of the original TCN,using the Leaky ReLU activation function to replace the ReLU function;and the improved TCN is connected with 1DCNN.Through the analysis of simulation results,the model can not only identify emitter signals quickly,but also have a high accuracy rate of identification,which can effectively balance the recognition speed and model recognition accuracy.