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Mobile Information Systems
Volume 10 (2014), Issue 3, Pages 307-319
http://dx.doi.org/10.3233/MIS-130185

Parameter Estimation for Propagation along Random Rough Surface by Using Line of Sight Data

Kazunori Uchida,1 Masafumi Takematsu,2 Jun-Hyuck Lee,2 and Junichi Honda3

1Department of Information and Communication Engineering, Fukuoka Institute of Technology, Higashi-Ku, Fukuoka, Japan
2Graduate School of Engineering, Fukuoka Institute of Technology, Higashi-Ku, Fukuoka, Japan
3Surveillance and Communications Department, Electronic Navigation Research Institute, Tokyo, Japan

Received 5 November 2013; Accepted 5 November 2013

Copyright © 2014 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This paper is concerned with a numerical procedure to estimate two parameters, amplitude modification factor α and propagation order of distance β, for electromagnetic (EM) propagation in complicated natural environments such as random rough surface (RRS). These two parameters are key parameters when we simulate field distributions along various types of RRS based on 1-ray model. We assume that the former parameter α can be evaluated by the visual planar angles of illuminated lines in case of 1D RRS and by the visual solid angles of illuminated planes in case of 2D RRS. We also assume that the latter parameter β can be estimated not only by base station (BS) antenna height, similar to Okumura-Hata model simulating EM propagation in urban and suburban areas, but also by mobile station (MS) antenna height. In order to demonstrate validity of the proposed parameter estimation, we compare the numerical field distributions obtained by the 1-ray model using estimated two parameters with those computed by discrete ray tracing method (DRTM) which is an effective EM field solver. It is shown that both numerical results are in good agreement.