LPI Radar Waveform Recognition Based on Multi-Resolution Deep Feature Fusion

LPI Radar Waveform Recognition Based on Multi-Resolution Deep Feature Fusion

Deep neural networks are used as effective methods for the Low Probability of Intercept (LPI) radar waveform recognition. However, existing models' performance degrades seriously at low Signal-to-Noise Ratios (SNRs) because the effective features extracted by the networks are insufficient under...

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Bibliographic Details
Main Authors: Xue Ni, Huali Wang, Fan Meng, Jing Hu, Changkai Tong
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Radar waveform recognition
multi-resolution
feature fusion
FSST
convolutional neural network
Online Access:https://ieeexplore.ieee.org/document/9350641/

Internet

https://ieeexplore.ieee.org/document/9350641/

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