Performance Evaluation of Separated Aperture Sensor GPR System for Land Mine Detection

Moustafa, K. H.; Hussein, Khalid F. A.

doi:10.2528/pier07022607

Cited by 13 publications

(9 citation statements)

References 15 publications

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“…Ground penetrating radar (GPR) has been broadly used in many civilian and military applications in order to nondestructively investigate the subsurface property, i.e., in geological and archeological surveys, for detecting buried objects and locating subsurface cavities, due to its easy usage, quick operation, and low cost [1][2][3][4][5][6][7][8]. It is less destructive and can provide more information than other methods of exploration, i.e., borehole and drilling radar systems.…”

Section: Introductionmentioning

confidence: 99%

Two-Dimensional Microwave Tomographic Algorithm for Radar Imaging Through Multilayered Media

Zhang¹

2014

PIER

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Abstract-The imaging of targets embedded in a planar layered background media has been an important topic in subsurface and urban sensing. In this paper a fast and efficient tomographic algorithm for the imaging of targets embedded in a multilayered media is presented. The imaging algorithm is based on the first-order Born approximation and exploits the spectral multilayered media Green's function. The exploding reflection model is employed and then the Green's function is expanded in the spectral form to facilitate the easy implementation of the imaging algorithm with fast Fourier transform (FFT). The wave propagation effect due to the presence of the layered subsurface media is automatically taken into account in the imaging formulation through the multilayer media Green's function. The linearization of the inversion scheme and employment of FFT make the imaging algorithm suitable in several applications concerning the diagnostics of large probed domain and allow real-time processing. Representative examples are presented to show the effectiveness and efficiency of the proposed algorithm for radar imaging through multilayered media.

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Section: Introductionmentioning

confidence: 99%

Two-Dimensional Microwave Tomographic Algorithm for Radar Imaging Through Multilayered Media

Zhang¹

2014

PIER

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“…• The soil is assumed to be homogeneous with an electric conductivity of 0.02 S/m, a relative permittivity of 2.9 and a relative magnetic permeability of 1 [10].…”

Section: Domain Geometry and Propertymentioning

confidence: 99%

“…In the inverse problem, several studies have been undertaken in the frequency domain [7,8] as well as in the time domain [9,10]. However, the common point of these researches is the characterization of the buried objects to minimize false alarms due to the presence of nonexplosive metallic objects.…”

Section: Introductionmentioning

confidence: 99%

“…In this way, several methods have been explored. These developments include the work of [10] in which a separated GPR aperture sensor method is applied to detect buried targets by evaluating and comparing the electromagnetic coupling between the transmitting and receiving antennas. The authors used Finite Difference Time Domain (FDTD) for electromagnetic simulation.…”

Section: Introductionmentioning

confidence: 99%

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An Emi Inversing Problem for Landmine Characterization Based on Improved Particle Swarm Optimization and Finite Element Analysis

Matriche¹,

Féliachi²,

Zaoui³

et al. 2013

PIER B

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Abstract-This paper discusses the characterization of landmine by using the electromagnetic induction technique (EMI). The proposed approach is based on the identification of the physical and geometrical properties of a landmine, from the sensor response. But in such an identification, the inverse problem is unavoidable. At first, we begin by simulating the landmine signature by solving a direct problem using the finite element method which constitutes the direct model. After that, we determine the landmine characteristics by using an inverse model based on a cost function optimization. This model is based on an iterative process which coupling finite element analysis and Particles Swarm Optimization (PSO). In this step, we apply two PSO techniques: the Standard PSO (SPSO) and the Improved PSO (IPSO), and discuss the problem of local minima of the cost function. The proposed iterative model is applied to determine the conductivity, geometry, and depth of metallic landmine from its signature measured by EMI. The numerical solution gives good results for the identification of landmine.

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“…Many kinds of sensors are under investigation for landmine detection, e.g., multispectral sensor [4], hyperspectral sensor [5], infrared sensor [6], and ground penetrating radar (GPR) [7]. GPR is a promising technology which can detect both plastic and metal landmines.…”

Section: Introductionmentioning

confidence: 99%

Sparse Time-Frequency Representation Based Feature Extraction Method for Landmine Discrimination

Wang¹,

Song²,

Tian³

et al. 2013

PIER

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Abstract-Low-frequency ultra-wideband synthetic aperture radar is a promising technology for landmine detection. According to the scattering characteristics of body-of-revolution (BOR) along with azimuth angles, a discriminator based on Bayesian decision rule is proposed, which uses sequential features, i.e., double-hump distance. First, the algorithm estimates the target scatterings in all azimuth angles based on regions of interest. Second, sequential aspect features are extracted by sparse time-frequency representation. Third, the distributions of features are obtained by training samples, and then the posterior probability of landmine class is computed as an input to the classifier adopting Mahalanobis distance. The experimental results indicate that the proposed algorithm is effective in BOR target discrimination.

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Performance Evaluation of Separated Aperture Sensor GPR System for Land Mine Detection

Cited by 13 publications

References 15 publications

Two-Dimensional Microwave Tomographic Algorithm for Radar Imaging Through Multilayered Media

Two-Dimensional Microwave Tomographic Algorithm for Radar Imaging Through Multilayered Media

An Emi Inversing Problem for Landmine Characterization Based on Improved Particle Swarm Optimization and Finite Element Analysis

Sparse Time-Frequency Representation Based Feature Extraction Method for Landmine Discrimination

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