Anomaly Detection

Award Information
Agency: Department of Defense
Branch: Defense Advanced Research Projects Agency
Contract: W31P4Q-09-C-0278
Agency Tracking Number: 07SB2-0344
Amount: $742,077.00
Phase: Phase II
Program: SBIR
Awards Year: 2009
Solicitation Year: 2007
Solicitation Topic Code: SB072-020
Solicitation Number: 2007.2
Small Business Information
Black River Systems Company, Inc.
162 Genesee Street, Utica, NY, 13502
DUNS: 111305843
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Jeffrey Brandstadt
 Principal Investigator
 (315) 732-7385
 brandstadt@brsc.com
Business Contact
 Milissa Benincasa
Title: Vice President
Phone: (315) 732-7385
Email: benincasa@brsc.com
Research Institution
N/A
Abstract
Recent DoD programs have furthered intelligence, surveillance and reconnaissance (ISR) objectives by advancing the state-of-the-art in sensor resource management and target tracking. The majority of this work, however, has focused upon the problem of tracking a handful of high value targets for lengthy periods. There is a need to develop systems that detect anomalous activities that have the potential to be threatening or to be militarily significant. Such detections may result in high value target tracks, but the objective of this effort is to manage a constrained set of ISR assets to detect anomalous events. This requires the an automated resource manager to actively command sensors and modes, and to do so in a manner that de-conflicts parallel, competitive tasks. The sensor suite must simultaneously build normalcy models, detect anomalies, command sensor timeline to evaluate anomalies, and manage concurrent, high value tracks. Black River Systems proposes to develop a system architecture that manages sensor resources to execute four concurrent objectives: normalcy monitoring, anomaly detection, anomaly interrogation, and high value target track. Leveraging our tracking, sensor resource management, and simulation and modeling experience, we will demonstrate and analyze system performance through trade studies and simulations.

* information listed above is at the time of submission.

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