UNCLASSIFIED MARITIME DOMAIN AWARENESS: RESULTS OF AT SEA EXPERIMENTATION DURING SEACAT '18
Loading...
Authors
Sousa, Kristopher E.
Minter, Daniel
Subjects
maritime domain awareness
MDA
SeaVision
computer vision
SEACAT
MDA
SeaVision
computer vision
SEACAT
Advisors
Boger, Dan C.
Date of Issue
2019-03
Date
Publisher
Monterey, CA; Naval Postgraduate School
Language
Abstract
The purpose of this thesis is to conduct and observe experimentation, using the unclassified Common Operating Picture tool SeaVision, in conjunction with the Surveillance, Persistent Observation and Target Recognition (SPOTR) program created by Progeny. These systems together will utilize unclassified satellite imagery to detect, classify and identify vessels at sea using computer vision (CV) algorithms. The CV algorithms use imagery of vessels of interest (VOI) to create a three-dimensional model that is used to detect and identify vessels in the satellite imagery. Images and information regarding these vessels were gathered from unclassified sources for analysis and building of the three-dimensional models. The information-gathering process would benefit from infusion or access to intelligence information for building image libraries of VOI. The technology, while still maturing, shows potential for implementation in various facets onboard surveillance platforms and unmanned surface and air vehicles.
Type
Thesis
Description
Series/Report No
Department
Information Sciences (IS)
Information Sciences (IS)
Organization
Identifiers
NPS Report Number
Sponsors
Funding
Format
Citation
Distribution Statement
Approved for public release; distribution is unlimited.
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.