Phase Screen Simulation Methods for Atmospheric and Ionospheric Modeling with MATLAB Implementation

Phase screen is a widely used technique for simulating random perturbations in the atmosphere and ionosphere, which introduces random phase variations to emulate refractive index fluctuations encountered by light waves or electromagnetic waves during propagation. Implementing this simulation in MATLAB hinges on constructing appropriate phase screen models while integrating visualization techniques to generate intuitive color images.

Fundamental Principles of Phase Screens The core of phase screens lies in describing random distributions of medium refractive index. Random phase screens are typically generated using power spectrum methods, where Kolmogorov spectrum or Von Karman spectrum are commonly employed for atmospheric turbulence simulation. Ionospheric disturbances may involve different spectral models depending on the random fluctuation characteristics of electron density.

MATLAB Implementation Approach Random Phase Generation: Based on Fourier transform methodology, first generate random complex matrices conforming to specific power spectra, then obtain spatial domain phase perturbations through inverse transformation. MATLAB implementation typically involves using fft2 and ifft2 functions with proper spectral filtering. Parameter Adjustment: Modify relevant parameters according to atmospheric or ionospheric characteristics, such as turbulence strength (Cn²) and outer scale (L₀), to control statistical properties of phase screens. This can be achieved through scaling factors in spectral domain calculations. Color Visualization: Map phase values to color spaces (like HSV or custom colormaps) and render results using imagesc or imshow functions to enhance discrimination between different phase regions. Custom colormaps can be created using MATLAB's colormap editor for optimal contrast.

Extended Applications Atmospheric Turbulence Simulation: Suitable for wavefront distortion studies in laser communications or astronomical imaging. Ionospheric Disturbance Analysis: Can assist in researching scattering effects of radio wave propagation. Dynamic Simulation: By generating phase screen sequences over time, time-varying disturbance processes can be simulated through iterative generation with parameter evolution.

The advantage of this method lies in its computational efficiency and flexibility in adapting to physical models of different media, making it an essential simulation tool in optical and radio wave propagation fields. The MATLAB implementation allows for rapid prototyping and parameter sensitivity analysis through script-based automation.