Specular propagation over rough surfaces: numerical assessment of Uscinski and Stanek's mean Green's function technique

Lai, Zhiguo; Janaswamy, Ramakrishna

doi:10.1080/17455030500499398

Cited by 4 publications

(3 citation statements)

References 12 publications

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“…A forward scattering approach in computing PF far from the transmitter location, whereas the randomness is in the generation of the randomly shaped perfectly conducting (PEC) surface, has conventionally been tackled with MC sampling [43], [46]. We have considered this application with sparse grids in [47].…”

Section: Discussionmentioning

confidence: 99%

Assessment of Adaptive Sparse Grid Collocation Methods in Wave Propagation Environments With Uncertainty

Ozbayat

Janaswamy

2014

IEEE Trans. Antennas Propagat.

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Sparse grid collocation methods are used for uncertainty quantification in electromagnetic propagation problems. The first application here involves waves propagating in lossy media with uncertain permittivities and permeabilities, for which several cases with increasing random-space dimensionality are exemplified. The objective in the second application is to compute expected signal strength above flat Earth surface at ranges far from transmitter location, where randomness is present due to uncertain refractivity of the atmosphere. Two different sparse grid algorithms are demonstrated throughout the paper, and the deterministic evaluators are accessed as a black box by the sparse grid algorithms. The difficult task of a priori method adaption is overcome by a first order check that enforces the black box solver only a few times. Through the results considered, strengths of the two algorithms are differentiated depending on the characteristics of the randomness. The advantage of a new routine used in this work is emphasized by showing its numerical contribution to the field estimation problem in a specific example. By means of the sparse grid methods used, we quantitatively provide the relative importance of each RV in contributing to the changes in the field distribution received at the observation range.Index Terms-Inhomogeneous atmosphere, parabolic equation method, radiowave propagation, random media, sparse grid collocation, split-step Fourier propagator, uncertainty quantification.

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Section: Discussionmentioning

confidence: 99%

Assessment of Adaptive Sparse Grid Collocation Methods in Wave Propagation Environments With Uncertainty

Ozbayat

Janaswamy

2014

IEEE Trans. Antennas Propagat.

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“…However, it is believed that the theory presented in the paper will lay the groundwork for obtaining approximate analytical solutions in a variety of situations. For instance, in lowgrazing angle propagation over a sea surface, one is interested in the mean field at certain distance from the transmitter [1], [35], and [43]. This problem is also of interest to underwater acoustic propagation [27].…”

Section: Discussionmentioning

confidence: 99%

“…The latter equality in (12) assumes that the initial data is differentiable. Equation (9) was used in [26] and [35] and solved numerically, although its derivation was not shown there. The auxiliary kernel K 0 (x; ξ) will be bounded if Lipschitz conditions are imposed on the function g(x) describing the rough surface.…”

Section: A Volterra Integral Equation Of the Second Kindmentioning

confidence: 99%

Direct Solution of Current Density Induced on a Rough Surface by Forward Propagating Waves

Janaswamy

2013

IEEE Trans. Antennas Propagat.

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Abstract-A new Volterra integral equation of the second kind with square integrable kernel is derived for paraxial propagation of radiowaves over a gently varying, perfectly conducting rough surface. The integral equation is solved exactly in terms of a infinite series and the necessary and sufficient conditions for the solution to exist and converge are established. Super exponential convergence of the Neumann series for arbitrary surface slope is established through asymptotic analysis. Expressions are derived for the determination of the number of terms needed to achieve a given accuracy, the latter depending on the parameters of the rough surface, the frequency of operation and the maximum range. Numerical results with truncated series are compared with that obtained by solving the integral equation numerically for a sinusoidal surface, Gaussian hill, and a random rough surface with Pierson-Moskowitz spectrum.

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Quantification of high dimensional uncertainty in propagation over random terrain

Ozbayat

Janaswamy

2013

2013 IEEE Antennas and Propagation Society International Symposium (APSURSI)

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Specular propagation over rough surfaces: numerical assessment of Uscinski and Stanek's mean Green's function technique

Cited by 4 publications

References 12 publications

Assessment of Adaptive Sparse Grid Collocation Methods in Wave Propagation Environments With Uncertainty

Assessment of Adaptive Sparse Grid Collocation Methods in Wave Propagation Environments With Uncertainty

Direct Solution of Current Density Induced on a Rough Surface by Forward Propagating Waves

Quantification of high dimensional uncertainty in propagation over random terrain

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