@inproceedings{2d380ee26b89403d976595118d405cec,
title = "Conceptual space modeling for space event characterization",
abstract = "This paper provides a method for characterizing space events using the framework of conceptual spaces. We focus specifically on estimating and ranking the likelihood of collisions between space objects. The objective is to design an approach for anticipatory decision support for space operators who can take preventive actions on the basis of assessments of relative risk. To make this possible our approach draws on the fusion of both hard and soft data within a single decision support framework. Contextual data is also taken into account, for example data about space weather effects, by drawing on the Space Domain Ontologies, a large system of ontologies designed to support all aspects of space situational awareness. The framework is coupled with a mathematical programming scheme that frames a mathematically optimal approach for decision support, providing a quantitative basis for ranking potential for collision across multiple satellite pairs. The goal is to provide the broadest possible information foundation for critical assessments of collision likelihood.",
author = "Chapman, \{Jeremy R.\} and David Kasmier and David Limbaugh and Gagnon, \{Stephen R.\} and Crassidis, \{John L.\} and James Llinas and Barry Smith and Cox, \{Alexander P.\}",
note = "Publisher Copyright: {\textcopyright} 2020 International Society of Information Fusion (ISIF).; 23rd International Conference on Information Fusion, FUSION 2020 ; Conference date: 06-07-2020 Through 09-07-2020",
year = "2020",
month = jul,
doi = "10.23919/FUSION45008.2020.9190163",
language = "English",
series = "Proceedings of 2020 23rd International Conference on Information Fusion, FUSION 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "Proceedings of 2020 23rd International Conference on Information Fusion, FUSION 2020",
address = "United States",
}