Results 21 to 30 of about 457 (225)
A Wasserstein Distance-Based Cost-Sensitive Framework for Imbalanced Data Classification [PDF]
Radioengineering, 2023 Class imbalance is a prevalent problem in many real-world applications, and imbalanced data distribution can dramatically skew the performance of classifiers.
R. Feng, H. Ji, Z. Zhu, L. Wang
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Remote SensingTo address the issue associated with poor accuracy rates for specific emitter identification (SEI) under low signal-to-noise ratio (SNR) conditions, where the single-dimension radar signal characteristics are severely affected by noise, we propose an ...
Zehuan Jing +5 more
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Intra-Pulse Modulation Classification of Radar Emitter Signals Based on a 1-D Selective Kernel Convolutional Neural Network [PDF]
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 learning-based methods, especially convolutional neural networks (CNN), have been used in ...
Shibo Yuan, Bin Wu 0024, 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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Acta Physica Polonica A, 2011 The paper presents a novel approach, based on the wavelet decomposition and the learning vector quantisation algorithm, to automatic classification of signals with linear frequency modulation, generated by radar emitters.
Świercz, E.
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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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Deep Learning Techniques in Radar Emitter Identification
, 2023 In the field of electronic warfare (EW), one of the crucial roles of electronic intelligence is the identification of radar signals. In an operational environment, it is very essential to identify radar emitters whether friend or foe so that appropriate ...
Gupta, Preeti, Kakde, O G, Jain, Pooja
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, 2022 The automatic classification of radar waveform is a fundamental technique in electronic countermeasures (ECM).Recent supervised deep learning-based methods have achieved great success in a such classification task.However, those methods require enough labeled samples to work properly and in many circumstances, it is not available.To tackle this problem,
Feng, HanCong +4 more
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Radar Spectrum Image Classification Based on Deep Learning
, 2023 With the continuous development and progress of science and technology, the increasingly complex electromagnetic environment and the research and development of new radar systems have led to the emergence of various radar signals.
Kaizhuang Li +4 more
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Dilated CNN Design Approach for Extracting Multi-Scale Features in Radar Emitter Classification
IEEE Access, 2023 Radar emitter classification plays an increasingly significant role in the electronic reconnaissance system. Due to many convolutional neural network (CNN)-based approaches suffer from insufficient spatial receptive fields and inadequate feature ...
Enze Guo +4 more
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