Atmospheric Structure Simulation: An Autoregressive Model for Smooth Geophysical Power Spectra with Known Autocorrelation Function

Abstract

Within a defined domain, geophysical phenomena often are characterized by smooth continuous power spectral densities having a negative power law slope. Frequently, Fourier transform analysis has been employed to generate synthetic scenes from pseudorandom arrays by passing the stochastic data through a Fourier filter having a desired correlation structure and power spectral dependency. This report examines the possibility of producing synthetic structure by invoking autoregression analysis as contrasted with the Fourier method. Since computations that apply multidimensional fast Fourier transforms to large data arrays consume enormous resources and time, the goal of this study is to seek an alternative method to reduce the computational burden. Future editions of the Phillips Laboratory Strategic High Altitude Atmospheric Radiance Code (SHARC) will feature an ability to calculate structured radiance. The methods explored herein provide a process that can complement or in some cases supplement methods presently being used.

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Document Details

Document Type
Technical Report
Publication Date
Feb 05, 1993
Accession Number
ADA276691

Entities

People

  • James H. Brown

Organizations

  • Phillips Laboratory

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Altitude
  • Autocorrelation
  • Computations
  • Computer Programs
  • Data Science
  • Equations
  • Fast Fourier Transforms
  • Frequency
  • Geological Phenomena
  • High Altitude
  • Power Spectra
  • Radiance
  • Simulations
  • Spectra
  • Two Dimensional
  • White Noise

Readers

  • Image Processing and Computer Vision.
  • Statistical inference.
  • Theoretical Analysis.