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Realistic Covariance Prediction For the Earth Science ConstellationsRoutine satellite operations for the Earth Science Constellations (ESC) include collision risk assessment between members of the constellations and other orbiting space objects. One component of the risk assessment process is computing the collision probability between two space objects. The collision probability is computed via Monte Carlo techniques as well as numerically integrating relative probability density functions. Each algorithm takes as inputs state vector and state vector uncertainty information for both objects. The state vector uncertainty information is expressed in terms of a covariance matrix. The collision probability computation is only as good as the inputs. Therefore, to obtain a collision calculation that is a useful decision-making metric, realistic covariance matrices must be used as inputs to the calculation. This paper describes the process used by NASA Goddard's Earth Science Mission Operations Project to generate realistic covariance predictions for three of the ESC satellites: Aqua, Aura, and Terra
Document ID
20070010585
Acquisition Source
Goddard Space Flight Center
Document Type
Conference Paper
Authors
Duncan, Matthew
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Long, Anne
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Date Acquired
August 23, 2013
Publication Date
January 1, 2006
Subject Category
Earth Resources And Remote Sensing
Meeting Information
Meeting: AAS/AIAA Astronomical Specialist Conference
Location: Keystone, CO
Country: United States
Start Date: August 21, 2006
End Date: August 24, 2006
Sponsors: American Inst. of Aeronautics and Astronautics, American Astronomical Society
Distribution Limits
Public
Copyright
Other

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