Radio Frequency Interference Estimation using Transfer Function Based Dipole Moment Model
Dipole moment model is widely used to represent real noise source to estimate near field coupling between noise source and the victim antenna. However, direct full wave simulation of large number of dipole moment is often very time-consuming. Also, another set of full wave simulation is needed if parameters change. A more scalable approach is needed. In this paper, a transfer function based dipole moment model is proposed to solve this issue. The proposed method only needs one-time full wave simulation. The results obtained from this one-time simulation can be reused for other cases if the same antenna structure is used. The proposed method will use the simulation results to construct transfer functions. The method is implemented in CST where several high performance computing methods are available. The validation of a test board with both simulation and measurement data is also provided.
Q. Huang et al., "Radio Frequency Interference Estimation using Transfer Function Based Dipole Moment Model," Proceedings of the 2018 IEEE International Symposium on Electromagnetic Compatibility and 2018 IEEE Asia-Pacific Symposium on Electromagnetic Compatibility (2018, Singapore, Singapore), pp. 115 - 120, Institute of Electrical and Electronics Engineers (IEEE), May 2018.
The definitive version is available at https://doi.org/10.1109/ISEMC.2018.8393750
2018 IEEE International Symposium on Electromagnetic Compatibility and 2018 IEEE Asia-Pacific Symposium on Electromagnetic Compatibility, EMC/APEMC (2018: May 14-15, Singapore, Singapore)
Electrical and Computer Engineering
Electromagnetic Compatibility (EMC) Laboratory
National Science Foundation (U.S.)
Keywords and Phrases
Dipole-moment model; Near-field coupling; Near-field scanning; Radio-frequency interference; Transfer function
International Standard Book Number (ISBN)
Article - Conference proceedings
© 2018 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
01 May 2018