Conceptual Spaces for Space Event Characterization via Hard and Soft Data Fusion

AIAA (American Institute of Aeronautics and Astronautics) Scitech 2021 Forum (2021)
  Copy   BIBTEX

Abstract

The overall goal of the approach developed in this paper is to estimate the likelihood of a given kinetic kill scenario between hostile spacebased adversaries using the mathematical framework of Complex Conceptual Spaces Single Observation. Conceptual spaces are a cognitive model that provide a method for systematically and automatically mimicking human decision making. For accurate decisions to be made, the fusion of both hard and soft data into a single decision framework is required. This presents several challenges to this data fusion framework. The first is the challenge involved in handling multiple complex terminologies, which is addressed by drawing on a set of Space Domain Ontologies. Another challenge is the complex combinatorics involved when considering all possible feature combinations. This can be mitigated by using integer linear programming optimization that is outlined by the Complex Conceptual Spaces Single Observation mathematical model framework. A third challenge is the complicated physics that is involved in a spacecraft collision that must be addressed to obtain a better understanding of threat assessment. Overcoming these various challenges allows for a quantitative ranking for the potential of a kinetic kill collision across multiple spacecraft pairs. In addition to overcoming these challenges this paper will break down threat assessment into four domains and identify a ranking of threat both for each individual domain and for the four domains combined. Simulation results are shown to verify the developed concepts.

Other Versions

No versions found

Links

PhilArchive

External links

  • This entry has no external links. Add one.
Setup an account with your affiliations in order to access resources via your University's proxy server

Through your library

Similar books and articles

Implementing Dempster-Shafer Theory for property similarity in Conceptual Spaces modeling.Jeremy R. Chapman, John L. Crassidis, James Llinas, Barry Smith & David Kasmier - 2022 - Sensor Systems and Information Systems IV, American Institute of Aeronautics and Astronautics (AIAA) SCITECH Forum 2022.
The Space Domain Ontologies.Alexander P. Cox, C. K. Nebelecky, R. Rudnicki, W. A. Tagliaferri, J. L. Crassidis & B. Smith - 2021 - In Alexander P. Cox, C. K. Nebelecky, R. Rudnicki, W. A. Tagliaferri, J. L. Crassidis & B. Smith, National Symposium on Sensor & Data Fusion Committee.
The Space Object Ontology.Alexander P. Cox, Christopher Nebelecky, Ronald Rudnicki, William Tagliaferri, John L. Crassidis & Barry Smith - 2016 - In Alexander P. Cox, Christopher Nebelecky, Ronald Rudnicki, William Tagliaferri, John L. Crassidis & Barry Smith, 19th International Conference on Information Fusion (FUSION 2016). IEEE.

Analytics

Added to PP
2021-01-09

Downloads
837 (#30,003)

6 months
139 (#37,180)

Historical graph of downloads
How can I increase my downloads?

Author Profiles

David Kasmier
University at Buffalo
Barry Smith
University at Buffalo
Alexander Cox
Australian National University

Citations of this work

No citations found.

Add more citations

References found in this work

The Space Object Ontology.Alexander P. Cox, Christopher Nebelecky, Ronald Rudnicki, William Tagliaferri, John L. Crassidis & Barry Smith - 2016 - In Alexander P. Cox, Christopher Nebelecky, Ronald Rudnicki, William Tagliaferri, John L. Crassidis & Barry Smith, 19th International Conference on Information Fusion (FUSION 2016). IEEE.

Add more references