Computer vision and computational intelligence for real-time multi-modal space domain awareness

Mark Bolden, Paul Schumacher, David Spencer, Islam Hussein, Matthew Wilkins, Christopher Roscoe

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents a computer vision and computational intelligence approach to space domain awareness. The approach is specifically designed to produce probabilistic density functions and state estimates in real-time for objects within the domain. PDFs are also generated for regions where there are no objects, and where there is insufficient information to assert object existence. The approach is dynamic and naturally adapts to changes of state to include maneuvering objects. The processing speed of the approach is independent of the number of objects, instead only dependent on the size of the domain, the accuracy desired in all dimensions, and the computational architecture.

Original languageEnglish (US)
Title of host publicationSpaceflight Mechanics 2017
EditorsJon A. Sims, Frederick A. Leve, Jay W. McMahon, Yanping Guo
PublisherUnivelt Inc.
Pages2165-2178
Number of pages14
ISBN (Print)9780877036371
StatePublished - Jan 1 2017
Event27th AAS/AIAA Space Flight Mechanics Meeting, 2017 - San Antonio, United States
Duration: Feb 5 2017Feb 9 2017

Publication series

NameAdvances in the Astronautical Sciences
Volume160
ISSN (Print)0065-3438

Other

Other27th AAS/AIAA Space Flight Mechanics Meeting, 2017
CountryUnited States
CitySan Antonio
Period2/5/172/9/17

All Science Journal Classification (ASJC) codes

  • Aerospace Engineering
  • Space and Planetary Science

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