Application of tilt correlation statistics to anisoplanatic optical turbulence modeling and mitigation

Abstract

Atmospheric optical turbulence can be a significant source of image degradation, particularly in long range imaging applications. Many turbulence mitigation algorithms rely on an optical transfer function (OTF) model that includes the Fried parameter. We present anisoplanatic tilt statistics for spherical wave propagation. We transform these into 2D autocorrelation functions that can inform turbulence modeling and mitigation algorithms. Using these, we construct an OTF model that accounts for image registration. We also propose a spectral ratio Fried parameter estimation algorithm that is robust to camera motion and requires no specialized scene content or sources. We employ the Fried parameter estimation and OTF model for turbulence mitigation. A numerical wave-propagation turbulence simulator is used to generate data to quantitatively validate the proposed methods. Results with real camera data are also presented.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jul 30, 2021
Source ID
10.1364/ao.418458

Entities

People

  • Michael A. Rucci
  • Richard Van Hook
  • Russell C Hardie
  • Santasri Bose-pillai

Organizations

  • Air Force Institute of Technology
  • Air Force Research Laboratory
  • University of Dayton

Tags

Fields of Study

  • Physics

Readers

  • Computational Modeling and Simulation
  • Computer Vision.
  • Radar Systems Engineering.