Performance Modeling of Feature Aided Trackers

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA8650-11-M-1123
Agency Tracking Number: F103-192-2631
Amount: $99,732.00
Phase: Phase I
Program: SBIR
Awards Year: 2011
Solitcitation Year: 2010
Solitcitation Topic Code: AF103-192
Solitcitation Number: 2010.3
Small Business Information
Sheet Dynamics, Limited
1775 Mentor Avenue, Suite 302, Cincinnati, OH, -
Duns: 96-473-04
Hubzone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Adam Nolan
 Chief Technical Officer
 (513) 631-0579
 adam.nolan@etegent.com
Business Contact
 Stuart Shelley
Title: Principle
Phone: (513) 631-0579
Email: stuart.shelley@etegent.com
Research Institution
 Stub
Abstract
The bandwidth of current and future image analysts is insufficient to ingest the vast quantity of data generated by staring sensing platforms. Because of this, signature exploitation algorithms need to play a role in the data processing chain to cue analysts to specific regions of interest within the imagery. For systems which utilize exploitation algorithms, there is a need to understand the ability and limitations under various conditions. We propose a feature aided tracker that is able to model its performance based on the current operating conditions. This performance model is a crucial component of any layered sensing architecture. BENEFIT: EO based tracking algorithms for security applications, crowd monitoring, consumer characterization, and traffic flow analysis all suffer from limited self diagnostics. Algorithms which are able to predict performance corresponding to specific operating conditions would be able to 1)optimize sensor collection 2)mitigate false alarms 3)allow fuzzy decision making and 4)allocate additional resources when needed.

* information listed above is at the time of submission.

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