Unclassified Maritime Domain Awareness: Results of At Sea Experimentation During SEACAT '18
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.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jun 01, 2019
- Accession Number
- AD1080417
Entities
People
- Daniel Minter
- Kristopher E. Sousa
Organizations
- Naval Postgraduate School