A Monte-Carlo FDTD Technique for Rough Surface Scattering

Hastings, Frank D.; Schneider, John B.; Broschat, Shira L.

doi:10.1109/tap.1995.481168

Cited by 121 publications

(79 citation statements)

References 29 publications

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“…The Monte-Carlo method (MCM), which is also known as the method of statistical trials [38], has been used in the past together with an integral equation formulation in the frequency domain [9] and with the FDTD method in the time domain [16,17] for the analysis of electromagnetic scattering involving a random rough surface. Most recently, a Monte-Carlo MPSTD algorithm is developed for the analysis of scattering from a 2D cylinder buried below a random rough surface [32].…”

Section: Monte-carlo Statistic Averagementioning

confidence: 99%

“…As an effective time-domain algorithm, the Monte-Carlo finite difference time-domain method (FDTD) method has been developed for determining the scattering from a moderately rough surface alone [16] and the bistatic scattering from a 3D object over a random rough surface [17,18]. In contrast to the surface integral equation formulation, the FDTD approach is more effective for modeling complex inhomogeneous geometries.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Analysis of Scattering From Three-Dimensional Objects Buried Below a Random Rough Surface by Monte-Carlo MPSTD Method

Liu¹,

Dai²,

Xu³

2013

PIER B

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Abstract-This paper presents a Monte-Carlo multidomain pseudospectral time-domain (MPSTD) algorithm developed for the analysis of scattering from a three dimensional (3D) object buried below a random rough surface separating two half spaces. In the development, special attention is paid to the 3D computation domain decomposition and subdomain mapping involving the random rough surface as well as the subdomain patching along the rough surface. The Mote-Carlo MPSTD algorithm is then employed to determine the scattering of 3D objects of various shapes and electromagnetic properties; embedded in the lower half space with different permittivity and the roughness of the random rough surface may vary. Sample numerical results are presented, validated, and analyzed. Through the analysis, it is observed that the roughness of the random rough surface and the electromagnetic properties of the lower half space can significantly affect the scattered signature of the buried object.

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Section: Monte-carlo Statistic Averagementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Analysis of Scattering From Three-Dimensional Objects Buried Below a Random Rough Surface by Monte-Carlo MPSTD Method

Liu¹,

Dai²,

Xu³

2013

PIER B

View full text Add to dashboard Cite

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“…One solution to this problem is to consider illumination by a beam [4]- [7]. This is often employed as the incident field in frequency-domain integral-equation solvers [4]- [6].…”

Section: Truncating the Surfacementioning

confidence: 99%

“…However, the vast majority of work on rough-surface scattering has been addressed in the frequency domain [4]- [7]. Moreover, previously, most such work has addressed the rough-surface scattering problem alone, without consideration of scattering from a target buried under such a surface.…”

Section: Introductionmentioning

confidence: 99%

Time-domain sensing of targets buried under a Gaussian, exponential, or fractal rough interface

Dogaru

Carin

2001

IEEE Trans. Geosci. Remote Sensing

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Abstract-We numerically examine subsurface sensing via an ultrawideband ground penetrating radar (GPR) system. The target is assumed to reside under a randomly rough air-ground interface and is illuminated by a pulsed plane wave. The underlying wave physics is addressed through application of the multiresolution time-domain (MRTD) algorithm. The scattered time-domain fields are parametrized as a random process and an optimal detection scheme is formulated, accounting for the clutter and target signature statistics. Detector performance is evaluated via receiver operating characteristics (ROCs) for variable sensor parameters (polarization and incident angle) and for several rough-surface statistical models.

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“…These studies have been performed primarily in the frequency domain, although there have been some recent time-domain investigations [7], [9]. The rough surface is usually parametrized as a random process (i.e., while the details of a particular realization of the surface are not known exactly, each surface is assumed to represent one realization of an ensemble, characterized by known statistics).…”

Section: Introductionmentioning

confidence: 99%

Optimal time-domain detection of a deterministic target buried under a randomly rough interface

Dogaru

Collins

Carin

2001

IEEE Trans. Antennas Propagat.

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Abstract-We consider pulsed plane-wave scattering from targets buried under a rough air-ground interface. The properties of the interface are parametrized as a random process with known statistics, and therefore the fields scattered from a particular surface constitute one realization of an ensemble, characterized by corresponding statistics. Moreover, since the fields incident upon a buried target must first penetrate the rough interface, they and the subsequent scattered fields are random processes as well. Based on this understanding, an optimal detector is formulated, accounting for the clutter and target-signature statistics (the former due to scattering at the rough surface, and the latter due to transmission); the statistics of these two processes are in general different. Detector performance is compared to that of a matched filter, which assumes the target signature is known exactly (i.e., nonrandom). The results presented here, as a function of angle and polarization, demonstrate that there is often a significant gain in detector performance if the target signature is properly treated as a random process.

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A Monte-Carlo FDTD Technique for Rough Surface Scattering

Cited by 121 publications

References 29 publications

Analysis of Scattering From Three-Dimensional Objects Buried Below a Random Rough Surface by Monte-Carlo MPSTD Method

Analysis of Scattering From Three-Dimensional Objects Buried Below a Random Rough Surface by Monte-Carlo MPSTD Method

Time-domain sensing of targets buried under a Gaussian, exponential, or fractal rough interface

Optimal time-domain detection of a deterministic target buried under a randomly rough interface

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