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
Sensors 2009, 9(10), 8109-8125; doi:10.3390/s91008109

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)
View Full-Text   |   Download PDF [161 KB, uploaded 21 June 2014]   |   Browse Figures


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.
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) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Share & Cite This Article

Further Mendeley | CiteULike
Export to BibTeX |
EndNote |
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.

View more citation formats

Related Articles

Article Metrics

For more information on the journal, click here


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