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Radar Emitter Signal Recognition Based on One-Dimensional Convolutional Neural Network with Attention Mechanism [PDF]
Sensors, 2020 As the real electromagnetic environment grows complex and the quantity of radar signals turns massive, traditional methods, which require a large amount of prior knowledge, are time-consuming and ineffective for radar emitter signal recognition.
Bin Wu +5 more
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A Knowledge Graph-Driven CNN for Radar Emitter Identification
Remote Sensing, 2023 In recent years, the rapid development of deep learning technology has brought new opportunities for specific emitter identification and has greatly improved the performance of radar emitter identification.
Yingchao Chen +5 more
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Remote Sensing, 2022 Intra-pulse modulation classification of radar emitter signals is beneficial in analyzing radar systems. Recently, convolutional neural networks (CNNs) have been used in classification of intra-pulse modulation of radar emitter signals, and the results ...
Shibo Yuan +4 more
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Few-Shot Radar Emitter Signal Recognition Based on Attention-Balanced Prototypical Network
Remote Sensing, 2022 In recent years, radar emitter signal identification has been greatly developed via the utilization of deep learning and has achieved significant improvements in identification accuracy. However, with the continuous emergence of complex regime radars and
Jing Huang +4 more
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Radar Emitter Recognition Based on Spiking Neural Networks
Remote SensingEfficient and effective radar emitter recognition is critical for electronic support measurement (ESM) systems. However, in complex electromagnetic environments, intercepted pulse trains generally contain substantial data noise, including spurious and ...
Zhenghao Luo +3 more
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Radar emitter multi-label recognition based on residual network
Defence Technology, 2022 In low signal-to-noise ratio (SNR) environments, the traditional radar emitter recognition (RER) method struggles to recognize multiple radar emitter signals in parallel.
Yu Hong-hai +4 more
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Progress in Radar Emitter Signal Deinterleaving
Leida xuebao, 2022 Radar emitter signal deinterleaving is a key technology for radar signal reconnaissance and an essential part of battlefield situational awareness. This paper systematically sorts out the mainstream technology of radar emitter signal deinterleaving.
Jinping SUI, Zhen LIU, Li LIU, Xiang LI
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Analyzing radar emitter signals with membrane algorithms
Mathematical and Computer Modelling, 2010 The analysis of radar emitter signals is a critical process in modern electronic reconnaissance systems. This paper proposes the application of a modified variant, called MQEPS, of the quantum-inspired evolutionary algorithm based on P systems (QEPS) to the time-frequency atom decomposition for analyzing radar emitter signals.
Gexiang Zhang
exaly +2 more sources
Prototype‐based method for incremental radar emitter identification
IET Radar, Sonar & Navigation, 2023 With the widespread use of radars, different types of radar emitters are being used in the real electromagnetic environment. Radar emitter identification (REI) is an important technique in spectrum management.
Xiao Han +3 more
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Survey of Deep Learning for Radar Emitter Identification Based on Small Sample [PDF]
Jisuanji kexue, 2022 Traditional radar emitter identification methods can no longer meet the needs of identifying new-system radar emitters in the complicate and changeable electromagnetic environment.Deep learning methods can effectively extract the intra-pulse features of ...
SU Dan-ning, CAO Gui-tao, WANG Yan-nan, WANG Hong, REN He
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