Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12666/811
Title: Complex permittivity estimation by bio-inspired algorithms for target identification improvement
Authors: Poyatos Martínez, D.
Escot Bocanegra, D.
Montiel, I.
Olmeda, I.
Keywords: NCTI;ANN;GA;PSO;Permittivity;Permeability;Free-space measurements
Issue Date: 14-May-2007
Publisher: Springer Link
DOI: 10.1007/978-3-540-73055-2_25
Published version: https://link.springer.com/chapter/10.1007/978-3-540-73055-2_25
Citation: Nature inspired Problem Solving Methods in Knowledge Engineering 4528: 1029
Abstract: Identification of aircrafts by means of radar when no cooperation exists (Non-Cooperative Target Identification, NCTI) tends to be based on simulations. To improve them, and hence the probability of correct identification, right values of permittivity and permeability need to be used. This paper describes a method for the estimation of the electromagnetic properties of materials as a part of the NCTI problem. Different heuristic optimization algorithms such as Genetic Algorithms (GA) and Particle Swarm Optimization (PSO), as well as other approaches like Artificial Neural Networks (ANN), are applied to the reflection coefficient obtained via free-space measurements in an anechoic chamber. Prior to the comparison with real samples, artificial synthetic materials are generated to test the performance of these bio-inspired algorithms.
URI: http://hdl.handle.net/20.500.12666/811
ISBN: 978-3-540-73054-5
Appears in Collections:(Espacio) Artículos
(Espacio) Comunicaciones de Congresos

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