Automated Satellite Image Navigation

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 uti...

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Bibliographic Details
Main Author: Bassett, Robert M.
Other Authors: NAVAL POSTGRADUATE SCHOOL MONTEREY CA
Format: Text
Language:English
Published: 1992
Subjects:
Online Access:http://www.dtic.mil/docs/citations/ADA262868
http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA262868
Description
Summary: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.