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

Neural Network Emulation of the Integral Equation Model with Multiple Scattering

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Received: 3 August 2009; in revised form: 29 September 2009 / Accepted: 12 October 2009 / Published: 15 October 2009
(This article belongs to the Special Issue Neural Networks and Sensors)
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: 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
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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.

AMA Style

Pulvirenti L, Ticconi F, Pierdicca N. Neural Network Emulation of the Integral Equation Model with Multiple Scattering. Sensors. 2009; 9(10):8109-8125.

Chicago/Turabian Style

Pulvirenti, Luca; Ticconi, Francesca; Pierdicca, Nazzareno. 2009. "Neural Network Emulation of the Integral Equation Model with Multiple Scattering." Sensors 9, no. 10: 8109-8125.


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