A radar signal modulation type recognition method based on Swin Transformer neural network
四川大学学报. 自然科学版, 2023 In this paper, based on the Swin Transformer neural network we propose a method for the recognition of modulation type of the Low Probability of Intercept (LPI) radar signal. We firstly perform the time-frequency transformation, that is to say, transform
DONG Zhang-Hua, ZHAO Shi-Jie, LAI Li
doaj
LPI Radar Detection Based on Deep Learning Approach with Periodic Autocorrelation Function. [PDF]
Sensors (Basel), 2023 Park DH, Jeon MW, Shin DM, Kim HN.
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Low Probability of Intercept (LPI) Radar Signal Identification Techniques
Bioscience Biotechnology Research Communications, 2021 openaire +1 more source
Time–Frequency Image-Based Overlapping LPI Radar Signal Detection and Recognition with LPI-YOLO
SensorsAccurate recognition of overlapping low-probability-of-intercept (LPI) radar signals under low signal-to-noise ratio (SNR) conditions remains a challenging problem in electronic reconnaissance.
Hongbin Pan +4 more
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Extremely High Frequency (EHF) Low Probability of Intercept (LPI) communication applications [PDF]
, 1990 A Commander-in-Chief U.S. Pacific Fleet letter to the Chief of Naval Operations, dated September 12, 1989, contains a Command and Control Studies and Analysis Program (C2STAP) proposal for EHF line-of-sight communications.
Belcher, Robert W.
core
Radar Signal Recognition Based on CSRDNN Network
IEEE AccessIt is essential to achieve the high-accuracy recognition of low probability of intercept (LPI) radar signals in modern electronic warfare. However, under low signal-to-noise ratio (SNR), the recognition accuracy of the LPI radar signals is relatively low.
Zheng Zhang +6 more
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Lack of ownership of mobile phones could hinder the rollout of mHealth interventions in Africa. [PDF]
Elife, 2022 Okano JT, Ponce J, Krönke M, Blower S.
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Recognition of intrapulse modulation mode in radar signal with BRN-EST
Journal of Electronic Science and TechnologyNeural network-based methods for intrapulse modulation recognition in radar signals have demonstrated significant improvements in classification accuracy. However, these approaches often rely on complex network structures, resulting in high computational
Yan Cheng, Ke Mei, Hao Zeng
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Adaptive Tracking of High-Maneuvering Targets Based on Multi-Feature Fusion Trajectory Clustering: LPI's Purpose. [PDF]
Sensors (Basel), 2022 Wei L, Chen J, Ding Y, Wang F, Zhou J.
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