@inproceedings{97d793aa628c435e9ad55daa67c4330f,
title = "Unsupervised Specific Emitter Identification Based on Feature Parameter Fusion and Adaptive Clustering",
abstract = "In recent years, satellite communication technology has achieved great development and the security threat becomes more severe. The identification of legal satellite emitters is important to enhance the security of satellite communication systems. In this paper, we propose an unsupervised specific emitter identification (SEI) method based on feature parameter fusion and adaptive clustering. We designed a feature extractor which fuses diverse feature parameter extraction methods. Then, an adaptive clustering algorithm is introduced to achieve higher accuracy and efficiency in non-cooperative communication scenarios. Experimental results show that the proposed method outperforms existing unsupervised SEI in terms of recognition accuracy.",
keywords = "Adaptive clustering, SEI, feature parameter fusion, radio frequency fingerprint, unsupervised deep learning",
author = "Yuechen Wang and Zunwen He and Mingjun Ma and Yan Zhang and Shanping Yu and Wancheng Zhang",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE/CIC International Conference on Communications in China, ICCC Workshops 2022 ; Conference date: 11-08-2022 Through 13-08-2022",
year = "2022",
doi = "10.1109/ICCCWorkshops55477.2022.9896666",
language = "English",
series = "2022 IEEE/CIC International Conference on Communications in China, ICCC Workshops 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "269--274",
booktitle = "2022 IEEE/CIC International Conference on Communications in China, ICCC Workshops 2022",
address = "United States",
}