Applications of Neural Networks in Electromagnetics
Applications of Neural Networks in Electromagnetics
A two-distribution compounded statistical model for Radar HRRP target recognition
IEEE Transactions on Signal Processing - Part I
IWINAC '09 Proceedings of the 3rd International Work-Conference on The Interplay Between Natural and Artificial Computation: Part I: Methods and Models in Artificial and Natural Computation. A Homage to Professor Mira's Scientific Legacy
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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.