Tracking of Resident Space Objects with Covariance Realism

Award Information
Agency:
Department of Defense
Branch
Air Force
Amount:
$99,918.00
Award Year:
2010
Program:
STTR
Phase:
Phase I
Contract:
FA9550-10-C-0062
Agency Tracking Number:
F09B-T11-0238
Solicitation Year:
2009
Solicitation Topic Code:
AF09-BT11
Solicitation Number:
2009.B
Small Business Information
Emergent Space Technologies, Inc
6301 Ivy Lane, Suite 720, Greenbelt, MD, 20770
Hubzone Owned:
N
Socially and Economically Disadvantaged:
N
Woman Owned:
N
Duns:
101537046
Principal Investigator:
Robert Bishop
Principal Investigator
(512) 471-8129
rhbishop@mail.utexas.edu
Business Contact:
Everett Cary Jr
VP of Operations
(301) 345-1535
everett.cary@emergentspace.com
Research Institution:
University of Texas-Austin
David Boerner, CRA
Office of Sponsored Projects
101 E 27th Street, Suite 4.300
Austin, TX, 78712
(512) 471-6305
Nonprofit college or university
Abstract
Covariance realism and consistency are critical to precision tracking and long-term orbit prediction of resident space objects (RSOs). This proposal tackles the key challenges that would yield realistic state estimation error covariance measures for tracking RSOs with relevant covariance consistency metrics. The anticipated result is a proposed estimation architecture that provides state estimation error covariance realism with proven covariance consistency. Using a building block approach including carefully developed mathematical models of the environment and sensors and employing linear covariance and Monte Carlo techniques, a quantitative analysis will illuminate the best filtering approach to further refine and develop in Phase II. The results of Phase I will establish the fundamentals of the tracking problem for RSOs using traditional and non-traditional measurements. What can be observed? What states and parameters should be in the tracking filter? What performance can be achieved given the current Space Surveillance Network coupled with our proposed estimation architecture? In Phase II we will investigate particle filters and advanced nonlinear filtering methods utilizing approximate solutions of the Fokker-Planck-Kolmogorov equations to address the problem of state estimation error covariance realism and test using actual measurement data. BENEFIT: Current methods for tracking and long-term orbit prediction of resident space objects are inadequate for future needs requiring timely and precise tracks for a very sizeable number of targets. Collision probability calculations, which are used to make mission-critical decisions about spacecraft maneuvers, rely on having realistic covariance data from the orbit determination process. The fundamental challenge is to create a tracking process that yields state estimation error covariance measures that reflect the true errors in the estimation process. The recursive tracking algorithms that produce realistic and consistent error covariances developed during Phase 2 will be developed into a software product that could be incorporated into Analytical Graphic, Inc. (AGI)’s Orbit Determination Toolkit (ODTK) as an add-on module or integrated into a Service Oriented Architecture (SOA) based ground system. This product could then be integrated into the Joint Space Operations Center (JSpOC) Mission System (JMS). The funding for Phase 3 could then be provided by the JMS program. Incorporating this software into ODTK as an add-on module would enable Emergent Space Technologies, Inc. to leverage the sales and marketing infrastructure of AGI to provide the widest possible dissemination and usage of the technology developed under this SBIR.

* information listed above is at the time of submission.

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