JOURNAL ARTICLE

One Dimensional Random Wave Propagation

Edmond Ghandour

Year: 1975 Journal:   SIAM Journal on Applied Mathematics Vol: 28 (4)Pages: 885-898   Publisher: Society for Industrial and Applied Mathematics

Abstract

We study wave propagation in a one-dimensional random medium whose index of refraction is characterized randomly and is assumed to have small fluctuations about the mean. The appropriate stochastic boundary value problem for the scattering region is transformed into a Cauchy type initial value problem for the boundary values of the random Green’s function. The stochastic differential equation derived is a first order, nonlinear equation of the Riccati type. The initial value problem is solved in two ways: (i) by conventional power series perturbation expansion, and (ii) by quasi-linearization. In both cases we consider the refracting medium to be characterized by a general stationary process in the broad sense, and for such a process, general expressions for the statistical properties of the reflected and transmitted amplitude waves are derived. In the former case the solutions obtained are uniformly valid for $\lambda < O( 1/\varepsilon )$, $\lambda $ being the size of the scattering region and $\varepsilon \ll 1$, while in the second case the solutions are uniformly valid for all $\lambda $. As an example, we consider an Ornstein–Uhlenbeck process and its limiting white-Gaussian process, for which expressions for the mean power reflected and transmitted are obtained.

Keywords:
Mathematics Mathematical analysis Linearization Boundary value problem Initial value problem Stochastic process White noise Nonlinear system Physics Quantum mechanics

Metrics

3
Cited By
0.51
FWCI (Field Weighted Citation Impact)
9
Refs
0.60
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Topics

Numerical methods in inverse problems
Physical Sciences →  Mathematics →  Mathematical Physics
Underwater Acoustics Research
Physical Sciences →  Earth and Planetary Sciences →  Oceanography
Ocean Waves and Remote Sensing
Physical Sciences →  Earth and Planetary Sciences →  Oceanography

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