A Novel Method for Few-Shot Specific Emitter Identification in Non-Cooperative Scenarios
Author:
Affiliation:
1. Department of Information Fusion, Naval Aviation University, Yantai, China
2. The School of Aviation Basis, Naval Aviation University, Yantai, China
Funder
National Natural Science Foundation of China
Taishan Scholar Project of Shandong Province
Project through the Chinese National Key Laboratory of Science and Technology on Information System Security
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/10005208/09989379.pdf?arnumber=9989379
Reference31 articles.
1. Specific Emitter Identification Based on Variational Mode Decomposition and Spectral Features in Single Hop and Relaying Scenarios
2. Specific Emitter Identification via Hilbert–Huang Transform in Single-Hop and Relaying Scenarios
3. Convolutional Neural Network for Convective Storm Nowcasting Using 3-D Doppler Weather Radar Data
4. An Introduction to Deep Learning for the Physical Layer
5. Auto-CASH: A meta-learning embedding approach for autonomous classification algorithm selection
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1. Overcoming Data Limitations: A Few-Shot Specific Emitter Identification Method Using Self-Supervised Learning and Adversarial Augmentation;IEEE Transactions on Information Forensics and Security;2024
2. A Novel Meta-Learning Network With Adaptive Input Length and Attention Mechanism for Bearing Fault Diagnosis Under Different Working Conditions;IEEE Sensors Journal;2023-11-15
3. A Long Time Span-Specific Emitter Identification Method Based on Unsupervised Domain Adaptation;Remote Sensing;2023-11-02
4. Radio Frequency Fingerprinting Identification of Few-Shot Wireless Signals Based on Deep Metric Learning;Wireless Communications and Mobile Computing;2023-09-20
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