Individual Identification Algorithm for Radar Emitter Signal Based on DCGAN
The radar emitter individual recognition technology determines the carrier identity attributes by ex-tracting radar subtle features,which is one of the hot research directions in the field of electronic countermeas-ures.It is a mainstream method to identify the fingerprint of radar emitter by deep learning.However,the train-ing network requires a large number of data samples,and when the data samples are insufficient,the recogni-tion accuracy is not high.Based on this,an individual recognition algorithm of radar emitter signal based on deep convolutional generative adversarial networks(DCGAN)is proposed.Firstly,bispectral slice is used to ex-tract the features of the signal.Then DCGAN-based recognition network is constructed.Finally,the validity of the algorithm is verified by real data.The experimental results show that under the condition of severe sample loss,the proposed algorithm can recognize radar emitter under small sample conditions,with a recognition accu-racy of 90％,fully meeting the daily needs.
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