Hybrid Threat and Anomaly Diagnostics for Spacecraft Autonomy

Award Information
Agency:
Department of Defense
Branch
Air Force
Amount:
$99,903.00
Award Year:
2010
Program:
SBIR
Phase:
Phase I
Contract:
FA9453-10-M-0162
Award Id:
97266
Agency Tracking Number:
F093-087-1682
Solicitation Year:
n/a
Solicitation Topic Code:
AF 09-087
Solicitation Number:
n/a
Small Business Information
1410 Sachem Place, Suite 202, Charlottesville, VA, 22901
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
120839477
Principal Investigator:
RichardAdams
Sr. Research Scientist
(434) 973-1215
adams@bainet.com
Business Contact:
ConnieHoover
General Manager
(434) 973-1215
barron@bainet.com
Research Institute:
n/a
Abstract
Barron Associates Incorporated proposes development of a hybrid satellite threat and anomaly diagnostics system that leverages the advantages of constraint-based inference engines as well as specialized quantitative model-based and process history-based techniques. The hybrid methodology incorporates the output of tailored sensor classification and fault isolation routines as "smart monitors," providing accuracy for critical subsystems. These monitors feed a general inference engine that fuses the information with behavioral representations of other components in a hierarchical, scalable model. We propose applying this approach to a near-term flight demonstration on an Air Force satellite. In Phase I, we will make modifications to the inference engine necessary to incorporate the smart monitors. At the same time, we will develop tailored diagnostics and behavioral models for the mission. This initial effort will enable software implementation and on-orbit testing in Phase II. BENEFIT: Barron Associates will pursue commercialization of the proposed technology through a three-pronged approach. First, the effort will open consulting services and contract R&D opportunities for providing satellite manufacturers with tailored diagnostics. Second, by enabling "smart monitors" to be integrated into a general inference engine, the program will make our neural network software and FDI tools accessible to a broader customer base and a wider range of applications. Finally, we will pursue direct opportunities to commercialize advanced diagnostics hardware in spin-off ventures that leverage the algorithms developed in the proposed program.

* information listed above is at the time of submission.

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