[HTML][HTML] Radar emitter multi-label recognition based on residual network
Y Hong-hai, Y ** LPI radar signals based on multi-instance multi-label learning
In an ever-increasingly complex electromagnetic environment, multiple low probability of
intercept (LPI) radar emitters may transmit their own signals simultaneously on similar …
intercept (LPI) radar emitters may transmit their own signals simultaneously on similar …
Residual attention-aided U-Net GAN and multi-instance multilabel classifier for automatic waveform recognition of overlap** LPI radar signals
Z Pan, S Wang, Y Li - IEEE Transactions on Aerospace and …, 2022 - ieeexplore.ieee.org
Automatic waveform recognition of overlap** 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 …
Semantic learning for analysis of overlap** 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 overlap** …
intercept (LPI) radar signals to overlap in time–frequency domains. Analyzing overlap** …
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 …
Cross model deep learning scheme for automatic modulation classification
Deep Neural Networks (DNNs) have achieved remarkable accuracy improvements for
automatic modulation classification. However, the employed networks often have millions of …
automatic modulation classification. However, the employed networks often have millions of …