Enhanced Space Object Detection Without Prior Knowledge of the Point Spread Function

Abstract

Since the point detector was created, other detection algorithms have been created that increase the probability of detection, while still keeping the same probability of false alarm. The point detector still has uses, such as when there is no prior knowledge of the point spread function (PSF). The matched filter correlator (MFC) detector is reliant on prior knowledge of the PSF. This has been an issue in cases where the PSF information is potentially inaccurate or unknown. This thesis utilizes MFC detector in a manner that it has never been used before, along with a new detection algorithm, the Pearson's correlation coefficient (PCC) detector, in order to estimate Fried's Seeing Parameter (r0) for a captured image. In previous studies, r0 is known or is assumed to be known. This new method of estimating r0 could yield higher probability of detection rates among certain space objects with little or no prior knowledge about the space object in question.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2021
Accession Number
AD1132445

Entities

People

  • Grant F Graupmann

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Air Platforms
  • Human Systems

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Atmospheric Motion
  • Coefficients
  • Correlators
  • Data Sets
  • Department Of Defense
  • Detection
  • Electrical Engineering
  • Engineering
  • False Alarms
  • Governments
  • Light Sources
  • Matched Filters
  • Probability
  • Space Force
  • Space Objects
  • Space Surveillance
  • Standards
  • United States
  • Warning Systems

Readers

  • Computer Vision.
  • Nuclear and Radiation Engineering.
  • Regression Analysis.

Technology Areas

  • Space
  • Space - Space Objects