Results 1 to 10 of about 624 (155)
Recognition of Noisy Radar Emitter Signals Using a One-Dimensional Deep Residual Shrinkage Network [PDF]
Sensors, 2021 Signal features can be obscured in noisy environments, resulting in low accuracy of radar emitter signal recognition based on traditional methods. To improve the ability of learning features from noisy signals, a new radar emitter signal recognition ...
Shengli Zhang +3 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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Remote Sensing, 2021 The intra-pulse modulation of radar emitter signals is a key feature for analyzing radar systems. Traditional methods which require a tremendous amount of prior knowledge are insufficient to accurately classify the intra-pulse modulations. Recently, deep
Shibo Yuan, Bin Wu, Peng Li
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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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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
Radar Emitter Signals Recognition and Classification with Feedforward Networks
Procedia Computer Science, 2013 AbstractA possible application of neural networks for timely and reliable recognition of radar signal emitters is investigated. In particular, a large data set of intercepted generic radar signal samples is used for investigating and evaluating several neural network topologies, training parameters, input and output coding and machine learning ...
Ivan Jordanov
exaly +2 more sources
Efficient FPGA Implementation of Convolutional Neural Networks and Long Short-Term Memory for Radar Emitter Signal Recognition [PDF]
SensorsIn recent years, radar emitter signal recognition has enjoyed a wide range of applications in electronic support measure systems and communication security.
Bin Wu +5 more
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A Specific Emitter Identification System Design for Crossing Signal Modes in the Air Traffic Control Radar Beacon System and Wireless Devices [PDF]
Sensors, 2023 To improve communication stability, more wireless devices transmit multi-modal signals while operating. The term ‘modal’ refers to signal waveforms or signal types. This poses challenges to traditional specific emitter identification (SEI) systems, e.g.,
Miyi Zeng +4 more
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Sensors, 2022 In this study, a feature analysis and extraction method was proposed for specific emitter identification based on the signal generation mechanisms of radar transmitters. The generation of radar signals by radar transmitters was analyzed theoretically and
Yilin Liu +4 more
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A Specific Emitter Identification Algorithm under Zero Sample Condition Based on Metric Learning
Remote Sensing, 2021 With the development of information technology in modern military confrontation, specific emitter identification has become a hot and difficult topic in the field of electronic warfare, especially in the field of electronic reconnaissance.
Peng Man +3 more
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