Automated Satellite Image Navigation

Abstract

This study investigated the automated satellite image navigation method (Auto-Avian) developed and tested by Spaulding (1990) at the Naval Postgraduate School. The Auto-Avian method replaced the manual procedure of selecting Ground Control Points (GCP's) with an autocorrelation process that utilizes the World Vector Shoreline (WVS) provided by the Defense Mapping Agency (DMA) as a string of GCP's to rectify satellite images. The automatic cross- correlation of binary reference (WVS) and search (image) windows eliminated the subjective error associated with the manual selection of GCP's and produced accuracies comparable to the manual method. This study expanded the scope of Spaulding's (1990) research. The worldwide application of the Auto-Avian method was demonstrated in three world regions (eastern North Pacific Ocean, eastern North Atlantic Ocean and Persian Gulf). Using five case studies, the performance of the Auto-Avian method on 'less than optimum' images (i.e., islands, coastlines affected by lateral distortion and/or cloud cover) was investigated.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1992
Accession Number
ADA262868

Entities

People

  • Robert M. Bassett

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Space

DTIC Thesaurus Topics

  • Artificial Satellites
  • Atlantic Ocean
  • Case Studies
  • Circular Orbits
  • Cloud Cover
  • Computer Programming
  • Computers
  • Correlation Techniques
  • Cross Correlation
  • Geography
  • Navigation
  • North Atlantic Ocean
  • North Pacific Ocean
  • Oceanography
  • Pacific Ocean
  • United States
  • World Geodetic System

Fields of Study

  • Environmental science

Readers

  • Computer Vision.
  • Geodesy
  • Oceanography.

Technology Areas

  • Space