Identification of the geometrical parameters of cylindrical targets hidden in GPR images using particle swarm optimization (PSO) algorithm

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AHMADI REZA; Nan Bedeh Sajjad

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Journal: ENGINEERING GEOLOGY Year:2018 | Volume:11 | Issue:1 Page(s): 81-94

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Title

Identification of the geometrical parameters of cylindrical targets hidden in GPR images using particle swarm optimization (PSO) algorithm

Author(s)

AHMADI REZA | Nan Bedeh Sajjad | Issue Writer Certificate

Keywords

Ground-penetrating radar (GPR)Q1

Forward modelingQ1

Hyperbolic responseQ1

Extraction of geometrical parameters of cylindrical targetsQ1

Particle swarm optimization (PSO) algorithmQ1

Abstract

The geophysical ground-penetrating radar (GPR) method is able to detect and identify shallow buried targets especially cylindrical type without any destruction of the medium. GPR method is based on sending the electromagnetic waves generally in the range of 1 MHz up to 1 GHz frequency into the earth and receiving reflected off various buried targets. In present research, this method has been used to identify geometrical parameters of buried cylindrical targets containing burial depth and radius. This task was done through the mathematical relationships between geometrical parameters of cylindrical targets with their GPR Hyperbolic response using the particle swarm optimization algorithm (PSO). To achieve this goal first, Forward modeling of GPR data by 2-D finite-difference time-domain (FDTD) method using GPRMAX was performed for several synthetic models corresponding to common targets in geotechnical applications and subsurface cylindrical installations. Also in the research, several field surveys were carried out over the well-known buried cylindrical targets in Isfahan University of Technology campus, moreover their GPR response was investigated after employing different processing sequences. In order to extract the geometrical parameters of the buried cylindrical targets in synthetic models and real surveys, the PSO algorithm was used in MATLAB environment. The algorithm performance for 7 produced synthetic models, including cylindrical targets made by different materials, radii and burial depth, as well as the real radargrams of GPR profiles in Isfahan University of Technology campus was verified leading to favorite and reasonable results for the synthetic models and real radargrams, respectively.

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APA: Copy

AHMADI, REZA, & Nan Bedeh, Sajjad. (2018). Identification of the geometrical parameters of cylindrical targets hidden in GPR images using particle swarm optimization (PSO) algorithm. ENGINEERING GEOLOGY, 11(1 ), 81-94. SID. https://sid.ir/paper/381494/en

Vancouver: Copy

AHMADI REZA, Nan Bedeh Sajjad. Identification of the geometrical parameters of cylindrical targets hidden in GPR images using particle swarm optimization (PSO) algorithm. ENGINEERING GEOLOGY[Internet]. 2018;11(1 ):81-94. Available from: https://sid.ir/paper/381494/en

IEEE: Copy

REZA AHMADI, and Sajjad Nan Bedeh, “Identification of the geometrical parameters of cylindrical targets hidden in GPR images using particle swarm optimization (PSO) algorithm,” ENGINEERING GEOLOGY, vol. 11, no. 1 , pp. 81–94, 2018, [Online]. Available: https://sid.ir/paper/381494/en

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