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Autonomous Characterization Algorithms for Change Detection and Correlation (ACDC)

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA9453-14-M-0156
Agency Tracking Number: F141-123-1412
Amount: $150,000.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: AF141-123
Solicitation Number: 2014.1
Timeline
Solicitation Year: 2014
Award Year: 2014
Award Start Date (Proposal Award Date): 2014-06-20
Award End Date (Contract End Date): 2015-02-12
Small Business Information
20532 El Toro Rd Ste 303
Mission Viejo, CA 92692-
United States
DUNS: 825470987
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Mark Poole
 Chief Technology Officer
 (949) 716-4290
 mpoole@exoanalytic.com
Business Contact
 Holly Bertrand
Title: Chief Operating Officer
Phone: (949) 716-4290
Email: bertrand@exoanalytic.com
Research Institution
 Stub
Abstract

ABSTRACT: The modern warfighter requires freedom of action in space for friendly forces, and when necessary, the ability to defeat adversary efforts that interfere or attack US or allied space systems and to negate adversary space capabilities. Freedom of action in space is enabled by Space Situational Awareness (SSA). The SSA Decision Cycle information bottleneck forces warfighters to make critical decisions with old, inaccurate, or limited information on a limited number of resident space objects (RSOs). Today there is limited capability (and no real-time capability) to exploit EO/IR signatures for characterization. The inability to provide timely RSO characterization from non-resolved imagery creates gaps in our knowledge and forces reliance on more expensive and frequently less available means. The development of Autonomous Characterization Algorithms for Change Detection and Correlation (ACDC) is significant to the US Air Force and broader SSA community because it will enable automated processes to estimate the physical properties of space objects from passively collected photometric signatures. Improved understanding of RSO features (such as stability estimates, material estimates, shape estimates, and attitude estimates) will improve track custody, improve object correlations, reduce cross-tagging, and improve catalog accuracy. BENEFIT: The primary focus for commercialization of Autonomous Characterization Alogorithms for Change Detection and Correlation (ACDC) is to transition the capability to the Joint Space Operations Center (JSpOC). In particular, Team Exo will focus on ensuring a seamless integration of ACDC into ARCADE, which will enable operators to evaluate the impact of ACDC algorithms on their mission execution at JSpOC. In addition, automated characterization algorithms including stability estimation, attitude determination, and change detection have a variety of commercial and civil applications. Current and potential future uses include: detailed characterization for the intelligence community, automated asteroid detection and characterization, commercial space remote monitoring, and initial deployment identification and support for cubesats.

* Information listed above is at the time of submission. *

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