Sørensen, S.B., Zhou, Min, Meincke, Peter, Tynan, Niall and Gradziel, Marcin (2014) Efficient and accurate modeling of electrically large dielectric lens antennas using full-wave analysis. In: The 8th European Conference on Antennas and Propagation (EuCAP 2014). IEEE, pp. 3021-3024. ISBN 9788890701849
Preview
MG-Modeling-2014.pdf
Download (276kB) | Preview
Abstract
Two efficient analysis methods for the accurate modeling of electrically large dielectric lens antennas are presented. The first method is based on Double Physical Optics (PO), which takes into account an additional set of reflections within the lens, whereas the conventional PO method only accounts for one set. The second method relies on a higher-order Body of Revolution Method of Moments and is capable of providing a full-wave solution of a 100-wavelength dielectric lens antenna within 2 minutes on a laptop computer.
Item Type: | Book Section |
---|---|
Additional Information: | This work is supported by the European Space Agency under contract number 4000102522/10/NL/AF2011. Cite as: S. B. Sørensen, M. Zhou, P. Meincke, N. Tynan and M. L. Gradziel, "Efficient and accurate modeling of electrically large dielectric lens antennas using full-wave analysis," The 8th European Conference on Antennas and Propagation (EuCAP 2014), The Hague, 2014, pp. 3021-3024, doi: 10.1109/EuCAP.2014.6902464. |
Keywords: | modeling; dielectric lens; higher-order MoM; |
Academic Unit: | Faculty of Science and Engineering > Experimental Physics |
Item ID: | 13781 |
Identification Number: | 10.1109/EuCAP.2014.6902464 |
Depositing User: | Dr. Marcin Lukasz Gradziel |
Date Deposited: | 06 Jan 2021 16:30 |
Publisher: | IEEE |
Refereed: | Yes |
Funders: | European Space Agency |
Related URLs: | |
URI: | https://mural.maynoothuniversity.ie/id/eprint/13781 |
Use Licence: | This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here |
Repository Staff Only (login required)
Downloads
Downloads per month over past year