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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