Phase-modulated Rice model for statistical distributions of complex signals

Area of Science:

• Physics
• Acoustics
• Atmospheric Science

Background:

• The Rice model is standard for random wave scattering, handling weak and saturated regimes.
• It fails for broad spatial scales, like atmospheric turbulence, underestimating phase variations.

Purpose of the Study:

• Extend the Rice model to account for phase modulation from large-scale atmospheric inhomogeneities.
• Improve the description of complex signal statistics in scenarios with broad scattering scales.

Main Methods:

• Introduced random phase modulation to the basic Rice model.
• Derived joint and marginal distributions for complex signal statistics.
• Developed and analyzed approximations using Nakagami, wrapped normal, and von Mises distributions.

Main Results:

• The phase-modulated Rice model significantly improves agreement with simulated atmospheric sound propagation data.
• Approximations provide accurate representations for amplitude and phase distributions.
• The model effectively captures stronger phase variations caused by large-scale turbulence.

Conclusions:

• The phase-modulated Rice model offers a more accurate description of sound propagation in the atmospheric boundary layer.
• This extended model is crucial for scenarios with scattering across a wide range of spatial scales.
• The findings enhance understanding of wave propagation in complex, turbulent media.