High Resolution Imaging of Space Objects.

Abstract

This report describes the results of a research effort to investigate a method of obtaining high resolution images of space objects using earth-bound optical telescopes despite the turbulence of the atmosphere. The results of this research are an indication that using an iterative reconstruction algorithm, it is feasible to reconstruct diffraction-limited images from the Fourier modulus (or autocorrelation) data provided by stellar speckle interferometry. Experiments were performed on astronomical data. It was necessary to develop methods of compensating for systematic errors and noise in the data. These methods were applied to binary star data, and a diffraction-limited image was successfully reconstructed from the resulting Fourier modulus data. The uniqueness of images reconstructed from Fourier modulus data was explored using the theory of analytic functions. It was shown, among other things, that if an object or its autocorrelation consists of separated parts satisfying certain disconnection conditions, then it is usually uniquely specified by its Fourier modulus. A new method was developed for reconstructing the support of an object from the support of its autocorrelation; it involves taking the intersection of three translates of the autocorrelation support. For objects consisting of a number of separated points, a new method was developed for reconstructing the object. (Author)

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1981
Accession Number
ADA097359

Entities

People

  • James Fienup

Organizations

  • Environmental Research Institute of Michigan

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Analytic Functions
  • Binary Stars
  • Convex Sets
  • Crystal Structure
  • Data Processing
  • Delta Functions
  • Detection
  • Diffraction
  • High Resolution
  • Ions
  • Power Spectra
  • Space Objects
  • Spearography
  • Transfer Functions
  • Two Dimensional

Fields of Study

  • Physics

Readers

  • Approximation Theory.
  • Computer Vision.
  • Systems Analysis and Design

Technology Areas

  • Space
  • Space - Space Objects