Multi-Sensor Tracking and Fusion for Space Radar Application

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA8750-08-C-0181
Agency Tracking Number: F081-029-0704
Amount: $99,962.00
Phase: Phase I
Program: SBIR
Awards Year: 2008
Solicitation Year: 2008
Solicitation Topic Code: AF081-029
Solicitation Number: 2008.1
Small Business Information
162 Genesee Street, Utica, NY, 13502
DUNS: 111305843
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Mark Kozak
 Principal Investigator
 (315) 732-7385
Business Contact
 Milissa Benincasa
Title: Vice President
Phone: (315) 732-7385
Research Institution
Black River proposes a solution for Space Radar Multi-Sensor Tracking and Fusion that considers the specific advantages and challenges offered by LEO and MEO constellations. Our approach to this research topic is three-fold in that we will characterize the expected yield of the radar modes given various scenarios, develop a tracking and fusion methodology, and develop a closed loop end-to-end simulation architecture for performance evaluation. The multi-sensor/mode, multi-target tracking and fusion problem is addressed with a fully featured state-vector that consists of kinematic and pose estimates as well as feature attributes derived from HRR, SAR, and ISAR products. The fully featured state-vector is ideally a blueprint of the target, but in reality it is a sub-sampled vector with more dimensionality than kinematics alone. The advantage of the fully featured state-vector is that it can be used in the track-to-measurement assignment process or in a track-to-track fusion process. Another key component is an architecture that includes a sensor resource manager that is necessary to schedule the specific radar modes while optimizing collections and radar energy over multiple areas of interest.

* information listed above is at the time of submission.

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