Next Article in Journal / Special Issue
Guest Editor’s Concluding Remarks―Advances in Usage of ANN, Discussion of an Unsolved Problem, and Some Differences between Papers Written by Engineers and by Physicians
Previous Article in Journal
Efficient Aggregation of Multiple Classes of Information in Wireless Sensor Networks
Previous Article in Special Issue
Vehicle Signal Analysis Using Artificial Neural Networks for a Bridge Weigh-in-Motion System
Article Menu

Export Article

Open AccessArticle
Sensors 2009, 9(10), 8109-8125;

Neural Network Emulation of the Integral Equation Model with Multiple Scattering

Department of Electronic Engineering, Sapienza University of Rome, via Eudossiana 18, 00184 Rome, Italy
Author to whom correspondence should be addressed.
Received: 3 August 2009 / Revised: 29 September 2009 / Accepted: 12 October 2009 / Published: 15 October 2009
(This article belongs to the Special Issue Neural Networks and Sensors)
Full-Text   |   PDF [161 KB, uploaded 21 June 2014]


The Integral Equation Model with multiple scattering (IEMM) represents a well-established method that provides a theoretical framework for the scattering of electromagnetic waves from rough surfaces. A critical aspect is the long computational time required to run such a complex model. To deal with this problem, a neural network technique is proposed in this work. In particular, we have adopted neural networks to reproduce the backscattering coefficients predicted by IEMM at L- and C-bands, thus making reference to presently operative satellite radar sensors, i.e., that aboard ERS-2, ASAR on board ENVISAT (C-band), and PALSAR aboard ALOS (L-band). The neural network-based model has been designed for radar observations of both flat and tilted surfaces, in order to make it applicable for hilly terrains too. The assessment of the proposed approach has been carried out by comparing neural network-derived backscattering coefficients with IEMM-derived ones. Different databases with respect to those employed to train the networks have been used for this purpose. The outcomes seem to prove the feasibility of relying on a neural network approach to efficiently and reliably approximate an electromagnetic model of surface scattering. View Full-Text
Keywords: neural networks; surface scattering; radar sensors neural networks; surface scattering; radar sensors
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

Share & Cite This Article

MDPI and ACS Style

Pulvirenti, L.; Ticconi, F.; Pierdicca, N. Neural Network Emulation of the Integral Equation Model with Multiple Scattering. Sensors 2009, 9, 8109-8125.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top