Pulse repetition interval(PRI)modulation recognition and pulse sequence search are significant for effective electronic support measures.In modern electromagnetic environments,different types of inter-pulse slide rada...Pulse repetition interval(PRI)modulation recognition and pulse sequence search are significant for effective electronic support measures.In modern electromagnetic environments,different types of inter-pulse slide radars are highly confusing.There are few available training samples in practical situations,which leads to a low recognition accuracy and poor search effect of the pulse sequence.In this paper,an approach based on bi-directional long short-term memory(BiLSTM)networks and the temporal correlation algorithm for PRI modulation recognition and sequence search under the small sample prerequisite is proposed.The simulation results demonstrate that the proposed algorithm can recognize unilinear,bilinear,sawtooth,and sinusoidal PRI modulation types with 91.43% accuracy and complete the pulse sequence search with 30% missing pulses and 50% spurious pulses under the small sample prerequisite.展开更多
Recognition of pulse repetition interval(PRI)modulation is a fundamental task in the interpretation of radar intentions.However,the existing PRI modulation recognition methods mainly focus on single-label classificati...Recognition of pulse repetition interval(PRI)modulation is a fundamental task in the interpretation of radar intentions.However,the existing PRI modulation recognition methods mainly focus on single-label classification of PRI sequences.The prerequisite for the effectiveness of these methods is that the PRI sequences are perfectly divided according to different modulation types before identification,while the actual situation is that radar pulses reach the receiver continuously,and there is no completely reliable method to achieve this division in the case of non-cooperative reception.Based on the above actual needs,this paper implements an algorithm based on the recurrence plot technique and the multi-target detection model,which does not need to divide the PRI sequence in advance.Compared with the sliding window method,it can more effectively realize the recognition of the dynamically varying PRI mo dulation.展开更多
A static approach method method is used to get the spectrum expression of the pulse interval modulation signal.The expression is simple,has a clear physical concept and it has been confirmed by a simultaneous experiment.
开展脉冲重复间隔(Pulse Repetition Interval,PRI)模式识别工作是电子支援系统的一项重要任务。现代复杂电磁环境下,受雷达辐射源部署和接收设备本身影响,雷达脉冲丢失率极高,导致分选后PRI序列调制规律被破坏,现有的PRI模式识别方法...开展脉冲重复间隔(Pulse Repetition Interval,PRI)模式识别工作是电子支援系统的一项重要任务。现代复杂电磁环境下,受雷达辐射源部署和接收设备本身影响,雷达脉冲丢失率极高,导致分选后PRI序列调制规律被破坏,现有的PRI模式识别方法准确率不足。针对上述问题,从PRI序列还原角度出发,并结合PRI序列本质是时序序列的特点,提出GAIN-LSTM(Generative Adversarial Imputation Nets and Long Short Term Memory)网络架构,其先对丢失脉冲位置进行补全操作,恢复PRI调制规律,然后对还原后PRI序列进行调制模式识别。仿真结果表明,提出的GAIN-LSTM网络架构在脉冲丢失率70%时仍保持95%的正确识别率。展开更多
基金supported by the National Natural Science Foundation of China(61801143,61971155)the National Natural Science Foundation of Heilongjiang Province(LH2020F019).
文摘Pulse repetition interval(PRI)modulation recognition and pulse sequence search are significant for effective electronic support measures.In modern electromagnetic environments,different types of inter-pulse slide radars are highly confusing.There are few available training samples in practical situations,which leads to a low recognition accuracy and poor search effect of the pulse sequence.In this paper,an approach based on bi-directional long short-term memory(BiLSTM)networks and the temporal correlation algorithm for PRI modulation recognition and sequence search under the small sample prerequisite is proposed.The simulation results demonstrate that the proposed algorithm can recognize unilinear,bilinear,sawtooth,and sinusoidal PRI modulation types with 91.43% accuracy and complete the pulse sequence search with 30% missing pulses and 50% spurious pulses under the small sample prerequisite.
基金supported by the National Defense Science and Technology Outstanding Youth Science Fund Project(2018-JCJQ-ZQ-023)the Hunan Provincial Natural Science Foundation of Innovation Research Group Project(2019JJ10004)。
文摘Recognition of pulse repetition interval(PRI)modulation is a fundamental task in the interpretation of radar intentions.However,the existing PRI modulation recognition methods mainly focus on single-label classification of PRI sequences.The prerequisite for the effectiveness of these methods is that the PRI sequences are perfectly divided according to different modulation types before identification,while the actual situation is that radar pulses reach the receiver continuously,and there is no completely reliable method to achieve this division in the case of non-cooperative reception.Based on the above actual needs,this paper implements an algorithm based on the recurrence plot technique and the multi-target detection model,which does not need to divide the PRI sequence in advance.Compared with the sliding window method,it can more effectively realize the recognition of the dynamically varying PRI mo dulation.
文摘A static approach method method is used to get the spectrum expression of the pulse interval modulation signal.The expression is simple,has a clear physical concept and it has been confirmed by a simultaneous experiment.
文摘开展脉冲重复间隔(Pulse Repetition Interval,PRI)模式识别工作是电子支援系统的一项重要任务。现代复杂电磁环境下,受雷达辐射源部署和接收设备本身影响,雷达脉冲丢失率极高,导致分选后PRI序列调制规律被破坏,现有的PRI模式识别方法准确率不足。针对上述问题,从PRI序列还原角度出发,并结合PRI序列本质是时序序列的特点,提出GAIN-LSTM(Generative Adversarial Imputation Nets and Long Short Term Memory)网络架构,其先对丢失脉冲位置进行补全操作,恢复PRI调制规律,然后对还原后PRI序列进行调制模式识别。仿真结果表明,提出的GAIN-LSTM网络架构在脉冲丢失率70%时仍保持95%的正确识别率。
