舰船电子工程2019，Vol.39Issue(12)：92-95,4.DOI:10.3969/j.issn.1672-9730.2019.12.023
基于LSTM的雷达辐射源识别技术∗
Radar Emitter Recognition Technology Based on LSTM
摘要
Abstract
According to the continuous signal characteristic parameters of target recognizes type of radar emitter,which plays an important role in electronic warfare. The traditional method of machine learning requires a lot of artificial feature extraction and prior knowledge,and it is difficult to deal with timing problems. This paper identifies and classifies radar emitters based on the Long Short-Term Memory Network(LSTM)model. Through the simulation data,the deep LSTM network model is built on the Tensor?Flow platform. The continuous radar emitter signal characteristics are used as the input data and training of the network to realize the recognition of the radiation source. Experimental result shows that the constructed LSTM network model achieves better results. The average recognition rate is 93.2%.关键词
雷达辐射源识别/时序问题/LSTM网络/识别分类Key words
radar emitter recognition/sequence problem/LSTM network/recognition classification分类
信息技术与安全科学引用本文复制引用
刘括然..基于LSTM的雷达辐射源识别技术∗[J].舰船电子工程,2019,39(12):92-95,4.
