A smart meshing technique to speed up radar cross-section calculation of very large random rough surfaces

Rahman Sofiani, Hamid Heidar and Morteza Kazerooni

Journal of Electromagnetic Waves and Applications, 2015, vol. 29, issue 7, 941-952

Abstract: In this paper, smart triangular meshing algorithm (STMA) is proposed to calculate the radar cross-section of two-dimensional random rough surfaces. The focus is on the random sea surfaces. The electric field integral equation is solved by the method of moment (MOM) using the STMA meshing through breaking the surfaces into some sub-surfaces and including some modifications on the borders meshing. The Gaussian random distribution with Elfouhaily spectrum is applied to model the sea water as a rough surface. Respect to traditional triangular meshing techniques for MOM, this approach not only requires less memory and processing time, but also it is more efficient for larger surfaces using maximum capabilities of modern multi-core processors. We verify the method by comparing its output with FEKO suite 5.5 results. Finally, different cases are considered and the calculation time enhancement is examined.

Date: 2015
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/09205071.2015.1027415 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tewaxx:v:29:y:2015:i:7:p:941-952

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tewa20

DOI: 10.1080/09205071.2015.1027415

Access Statistics for this article

Journal of Electromagnetic Waves and Applications is currently edited by Mohamad Abou El-Nasr and Pankaj Kumar Choudhury

More articles in Journal of Electromagnetic Waves and Applications from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().