TY - GEN
T1 - Individual Intelligent Recognition Method Based on Fingerprint Features of Radar Emitter
AU - Liu, Zhongwei
AU - Gao, Hongwei
AU - Chen, Jie
AU - Zhou, Dongming
AU - Li, Yingchun
AU - Sun, Shuyan
AU - Xiang, Rongrong
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - Aiming at the problem of radar emitter individual recognition with unintentional modulation feature, a method of emitter fingerprint identification based on deep learning is proposed. In this method, the deep fingerprint features of radar emitter are extracted by deep Convolutional neural network, and the fingerprint feature library is constructed. Through similarity calculation, the individual recognition results of radar emitter signal are obtained. The results show that the new method can effectively identify both known and unknown emitter individuals.
AB - Aiming at the problem of radar emitter individual recognition with unintentional modulation feature, a method of emitter fingerprint identification based on deep learning is proposed. In this method, the deep fingerprint features of radar emitter are extracted by deep Convolutional neural network, and the fingerprint feature library is constructed. Through similarity calculation, the individual recognition results of radar emitter signal are obtained. The results show that the new method can effectively identify both known and unknown emitter individuals.
KW - Deep learning
KW - Fingerprint features
KW - Individual identification
KW - Radar emitter
UR - https://www.scopus.com/pages/publications/85181086312
U2 - 10.1109/Radar53847.2021.10028396
DO - 10.1109/Radar53847.2021.10028396
M3 - 会议稿件
AN - SCOPUS:85181086312
T3 - Proceedings of the IEEE Radar Conference
SP - 2137
EP - 2141
BT - 2021 CIE International Conference on Radar, Radar 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 CIE International Conference on Radar, Radar 2021
Y2 - 15 December 2021 through 19 December 2021
ER -