An Innovative Particle Swarm Optimization‐Based Approach for GPR Microwave Imaging

Salucci, M. and Poli, L. and Anselmi, N. and Massa, A. (2016) An Innovative Particle Swarm Optimization‐Based Approach for GPR Microwave Imaging. Technical Report. University of Trento.

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Abstract

This work presents an innovative microwave imaging technique for accurate and robust subsurface imaging. The proposed approach is based on the integration of a customized particle swarm optimization (PSO) algorithm within the iterative multi-scaling approach (IMSA), and exploits multiple frequency components extracted from ground penetrating radar (GPR) wideband data. The solution of the arising inverse scattering problem is yielded within a multi-frequency (MF) approach, allowing to exploit the intrinsic frequency diversity of GPR measurements in order to add information and mitigate the ill-posedness and non-linearity issues. Some numerical experiments are shown in order to assess the effectiveness of the proposed MF-IMSA-PSO method when dealing with the retrieval of unknown buried scatterers having different shape. Moreover, a comparison to a competitive state-of-the-art deterministic approach is shown, in order to highlight the benefits of exploiting a global optimization algorithm in minimizing the MF cost function.

Item Type: Monograph (Technical Report)
Uncontrolled Keywords: Ground Penetrating Radar (GPR), Inverse Scattering (IS), Multi-Frequency (MF), Particle Swarm Optimization (PSO), Stochastic Optimization, Wide-band Data, Iterative Multi Scaling Approach (IMSA)
Subjects: A Areas > A WC Next Generation Wireless Communications
M Methodologies > M EA Evolutionary Algorithms
URI: http://www.eledia.org/students-reports/id/eprint/733

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