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11 March 2022 Radar emitter individual identification
Haiyu Yang, Wenpu Guo, Kai Kang, Yixiao Zhang, Luhong Yan
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Proceedings Volume 12160, International Conference on Computational Modeling, Simulation, and Data Analysis (CMSDA 2021); 121601J (2022) https://doi.org/10.1117/12.2627671
Event: International Conference on Computational Modeling, Simulation, and Data Analysis (CMSDA 2021), 2021, Sanya, China
Abstract
Radar Emitter Individual Identification is a technique to extract the radio fingerprint features of radar by means of external feature measurement of the radar signal, in order to identify radar emitter individuals. In the past few years, the related theories and practical applications of radar emitter individual identification technology had been continuously improved, and the research on radio frequency fingerprint extraction methods has made great progress. Based on domestic and foreign academic achievements, the current research status is classified by deep learning methods, which are specifically divided into two types of traditional SEI methods and deep learning SEI methods. Finally, several potential research directions for Radar Emitter Individual Identification are analyzed and explored.
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Haiyu Yang, Wenpu Guo, Kai Kang, Yixiao Zhang, and Luhong Yan "Radar emitter individual identification", Proc. SPIE 12160, International Conference on Computational Modeling, Simulation, and Data Analysis (CMSDA 2021), 121601J (11 March 2022); https://doi.org/10.1117/12.2627671
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KEYWORDS
Radar
Feature extraction
Convolutional neural networks
Signal processing
Neural networks
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