Deep-learning for radar: A survey
Z Geng, H Yan, J Zhang, D Zhu - IEEE Access, 2021 - ieeexplore.ieee.org
A comprehensive and well-structured review on the application of deep learning (DL) based
algorithms, such as convolutional neural networks (CNN) and long-short term memory …
algorithms, such as convolutional neural networks (CNN) and long-short term memory …
An improved LPI radar waveform recognition framework with LDC-Unet and SSR-Loss
W Jiang, Y Li, M Liao, S Wang - IEEE Signal Processing Letters, 2021 - ieeexplore.ieee.org
Low probability of intercept (LPI) radar signals have been widely used in modern radars due
to the advantages of being hardly intercepted by non-cooperative receivers. Therefore, the …
to the advantages of being hardly intercepted by non-cooperative receivers. Therefore, the …
Residual attention-aided U-Net GAN and multi-instance multilabel classifier for automatic waveform recognition of overlapping LPI radar signals
Z Pan, S Wang, Y Li - IEEE Transactions on Aerospace and …, 2022 - ieeexplore.ieee.org
Automatic waveform recognition of overlapping low probability of intercept (LPI) radar
signals is an important and challenging task in electronic reconnaissance of the increasingly …
signals is an important and challenging task in electronic reconnaissance of the increasingly …
MIML-GAN: A GAN-based algorithm for multi-instance multi-label learning on overlapping signal waveform recognition
Existing studies for automatic waveform recognition of overlapping signals have mostly been
conducted in a supervised manner. Although demonstrating superior performance in recent …
conducted in a supervised manner. Although demonstrating superior performance in recent …
Automatic modulation recognition of dual-component radar signals using ResSwinT–SwinT network
B Ren, KC Teh, H An… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Automatic modulation recognition plays an important role in military and civilian
applications, identifying the modulation format of received signals before signal …
applications, identifying the modulation format of received signals before signal …
Semantic learning for analysis of overlapping LPI radar signals
The increasingly complex radio environment may cause the received low probability of
intercept (LPI) radar signals to overlap in time–frequency domains. Analyzing overlapping …
intercept (LPI) radar signals to overlap in time–frequency domains. Analyzing overlapping …
Intra-pulse modulation recognition of dual-component radar signals based on deep convolutional neural network
W Si, C Wan, Z Deng - IEEE Communications Letters, 2021 - ieeexplore.ieee.org
In an ever-increasingly complicated electromagnetic environment with explosive radar
signals density, accurate and fast recognition of dual-component radar signals has become …
signals density, accurate and fast recognition of dual-component radar signals has become …
Recognition and Estimation for Frequency-Modulated Continuous-Wave Radars in Unknown and Complex Spectrum Environments
K Chen, J Zhang, S Chen, S Zhang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The recognition and estimation of frequency-modulated continuous-wave (FMCW) radar
signals are critical for both military electronic countermeasures and civilian autonomous …
signals are critical for both military electronic countermeasures and civilian autonomous …
Multi-Label Radar Compound Jamming Signal Recognition Using Complex-Valued CNN with Jamming Class Representation Fusion
Y Meng, L Yu, Y Wei - Remote Sensing, 2023 - mdpi.com
In the complex battlefield electromagnetic environment, multiple jamming signals can enter
the radar receiver simultaneously due to the development of jammers and modulation …
the radar receiver simultaneously due to the development of jammers and modulation …
A reference signal-aided deep learning approach for overlapped signals automatic modulation classification
R Zhang, Y Zhao, Z Yin, D Li… - IEEE Communications …, 2023 - ieeexplore.ieee.org
Traditional likelihood-based and handcrafted feature-based methods for overlapped signals
automatic modulation classification (OS-AMC) suffer from the uncertainty of the overlapped …
automatic modulation classification (OS-AMC) suffer from the uncertainty of the overlapped …