Open-Set Radar Emitter Recognition via Deep Metric Autoencoder-Reference-Cited by-同舟云学术

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Open-Set Radar Emitter Recognition via Deep Metric Autoencoder

Published:2024-05-15 Issue:10 Volume:11 Page:18281-18291
ISSN:2327-4662
Container-title:IEEE Internet of Things Journal
language:
Short-container-title:IEEE Internet Things J.

Author:

Yang Chen¹^ORCID,Liu Huiling¹,Yang Shuyuan¹^ORCID,Feng Zhixi¹^ORCID,Tang Xiaogang²^ORCID,Zhang Feng³

Affiliation:

1. School of Artificial Intelligence, Xidian University, Xi’an, China

2. School of Aerospace Information, Space Engineering University, Beijing, China

3. Information Science Research Institute, China Electronics Technology Group Corporation, Beijing, China

Funder

National Natural Science Foundation of China

Science and Technology Innovation Team in Shaanxi Province of China

Foundation of Intelligent Decision and Cognitive Innovation Center of State Administration of Science, Technology and Industry for National Defense, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6488907/10528217/10460313.pdf?arnumber=10460313

Reference29 articles.

1. Online clustering algorithms for radar emitter classification

2. An Efficient Specific Emitter Identification Method Based on Complex-Valued Neural Networks and Network Compression

3. A Method for Radar Model Identification Using Time-Domain Transient Signals

4. Autmomatic Modulation Classification Using Combination of Genetic Programming and KNN

5. Phasma: An automatic modulation classification system based on Random Forest

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