TY - GEN
T1 - Interference Emission Sources Identification Approach Based on Basic Emission Waveform Theory
AU - Zhang, Fan
AU - Wang, Wang
AU - Xu, Hui
AU - Chen, Aixin
AU - Su, Donglin
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - With the rapid development of electronic technology in recent years, the application of electronic equipment or electronic system becomes more and more common, and these equipment or system produce a large number of intentional or unintentional electromagnetic emissions when they are working. In order to check the electromagnetic emission to avoid the impact on the surrounding electronic equipment or electronic system, the need of emitter identification arises, especially in the field of electromagnetic compatibility(EMC). This paper proposes a systematic radiation emitter identification approach. This approach divides the radiated emission data of equipment or system into three different kinds of components and the radiated emission data is classified according to the similarity of the three components. Three different kinds of electronic equipment radiation emission data are used to verify the proposed method. The classification accuracy for small samples of radiation emission data is 100%, which confirms the effectiveness of this method.
AB - With the rapid development of electronic technology in recent years, the application of electronic equipment or electronic system becomes more and more common, and these equipment or system produce a large number of intentional or unintentional electromagnetic emissions when they are working. In order to check the electromagnetic emission to avoid the impact on the surrounding electronic equipment or electronic system, the need of emitter identification arises, especially in the field of electromagnetic compatibility(EMC). This paper proposes a systematic radiation emitter identification approach. This approach divides the radiated emission data of equipment or system into three different kinds of components and the radiated emission data is classified according to the similarity of the three components. Three different kinds of electronic equipment radiation emission data are used to verify the proposed method. The classification accuracy for small samples of radiation emission data is 100%, which confirms the effectiveness of this method.
KW - Interference Emission Sources Identification
KW - feature extraction
KW - radiated emission components
UR - https://www.scopus.com/pages/publications/85146249541
U2 - 10.1109/IWS55252.2022.9977846
DO - 10.1109/IWS55252.2022.9977846
M3 - 会议稿件
AN - SCOPUS:85146249541
T3 - 2022 IEEE MTT-S International Wireless Symposium, IWS 2022 - Proceedings
BT - 2022 IEEE MTT-S International Wireless Symposium, IWS 2022 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 9th IEEE MTT-S International Wireless Symposium, IWS 2022
Y2 - 12 August 2022 through 15 August 2022
ER -