查看文章

In this paper, we propose a radar signal modulation algorithm to recognize three different radar signals amidst other wireless communication waveforms, including Barker, linear frequency modulation, and rectangular codes. First we extract the features of the original signal by computing its smoothed pseudo Wigner-Ville distribution. Second, we construct a transfer learning-based convolutional neural network over AlexNet to further extract features from the time-frequency images. Finally, a support vector machine classifier is applied for the signal classification. We also perform a similar analysis with models which use AlexNet for both feature extraction, and classification tasks. Results show that the proposed model which incorporates the linear classifier, achieves the highest recognition accuracy of 97.8%.