The modulation type of the radar pulse repetition interval(PRI)is an important means to analyze the working state and task of the radar.In order to solve the problem that common radar PRI modulation type recognition algorithms cannot identify un-known modulation types,an open-set recognition method for radar PRI modulation types based on improved extreme value machine(EVM)is proposed.Firstly,the residual network and bi-directional long short-term memory network is used to extract the features of PRI sequence.Secondly,combined with prototype learning,the feature extraction network is trained by distance-based cross-entropy loss and prototype loss.Finally,an improved EVM model is proposed by introducing a linear combination of known class features into the feature space to simulate the behavior of unknown classes.Experimental results show that compared with EVM,the proposed method can improve the recognition accuracy of radar PRI modulation type,and has good open-set adaptability in open electromagnetic environment.
关键词
脉冲重复间隔调制类型/开集识别/残差网络/双向长短时记忆/原型学习/极值理论
Key words
pulse repetition interval(PRI)modulation type/open-set recognition/residual network/bi-directional long short-term memory(BiLSTM)/prototype learning/extreme value theory
维普
万方数据