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 (GCPs) with an autocorrelation process that utilizes...

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Bibliographic Details
Main Author: Bassett, Robert M.
Other Authors: Wash, Carlyle H., Naval Postgraduate School, Meteorology, Durkee, Philip A.
Format: Thesis
Language:English
Published: Monterey, California. Naval Postgraduate School 1992
Subjects:
Online Access:https://hdl.handle.net/10945/23552
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spelling ftnavalpschool:oai:calhoun.nps.edu:10945/23552 2024-06-09T07:48:13+00:00 Automated satellite image navigation Bassett, Robert M. Wash, Carlyle H. Naval Postgraduate School Meteorology Durkee, Philip A. 1992-12 76 p. application/pdf https://hdl.handle.net/10945/23552 en_US eng Monterey, California. Naval Postgraduate School https://hdl.handle.net/10945/23552 This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States. Image navigation Binary correlation Automated landmarking Thesis 1992 ftnavalpschool 2024-05-15T00:26:04Z 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 (GCPs) with an autocorrelation process that utilizes the World Vector Shoreline (WVS) provided by the Defense Mapping Agency (DMA) as a "string" of GCPs to rectify satellite images. The automatic cross-correlation of binary references (WVS) and search (image) windows eliminated the subjective error associated with the manual selection of GCPs 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. The result indicated that utilizing the Auto-Avian method on these "less than optimum images" could achieve navigational accuracies approaching those obtained by Spaulding (1990). Approved for public release; distribution is unlimited. Lieutenant Commander, United States Navy http://archive.org/details/automatedsatelli1094523552 Thesis North Atlantic Naval Postgraduate School: Calhoun Pacific
institution Open Polar
collection Naval Postgraduate School: Calhoun
op_collection_id ftnavalpschool
language English
topic Image navigation
Binary correlation
Automated landmarking
spellingShingle Image navigation
Binary correlation
Automated landmarking
Bassett, Robert M.
Automated satellite image navigation
topic_facet Image navigation
Binary correlation
Automated landmarking
description 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 (GCPs) with an autocorrelation process that utilizes the World Vector Shoreline (WVS) provided by the Defense Mapping Agency (DMA) as a "string" of GCPs to rectify satellite images. The automatic cross-correlation of binary references (WVS) and search (image) windows eliminated the subjective error associated with the manual selection of GCPs 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. The result indicated that utilizing the Auto-Avian method on these "less than optimum images" could achieve navigational accuracies approaching those obtained by Spaulding (1990). Approved for public release; distribution is unlimited. Lieutenant Commander, United States Navy http://archive.org/details/automatedsatelli1094523552
author2 Wash, Carlyle H.
Naval Postgraduate School
Meteorology
Durkee, Philip A.
format Thesis
author Bassett, Robert M.
author_facet Bassett, Robert M.
author_sort Bassett, Robert M.
title Automated satellite image navigation
title_short Automated satellite image navigation
title_full Automated satellite image navigation
title_fullStr Automated satellite image navigation
title_full_unstemmed Automated satellite image navigation
title_sort automated satellite image navigation
publisher Monterey, California. Naval Postgraduate School
publishDate 1992
url https://hdl.handle.net/10945/23552
geographic Pacific
geographic_facet Pacific
genre North Atlantic
genre_facet North Atlantic
op_relation https://hdl.handle.net/10945/23552
op_rights This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
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