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Optimized Resource Allocation for Networked Sensors (OpeRA-Net)

Award Information
Agency: Department of Defense
Branch: Missile Defense Agency
Contract: HQ0006-07-C-7774
Agency Tracking Number: B063-009-0142
Amount: $100,000.00
Phase: Phase I
Program: SBIR
Awards Year: 2007
Solicitation Year: 2006
Solicitation Topic Code: MDA06-009
Solicitation Number: 2006.3
Small Business Information
TOYON RESEARCH CORPORATION
6800 Cortona Drive, Goleta, CA, 93117
DUNS: 054672662
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
Name: Kenan Ezal
Title: Senior Staff Analyst
Phone: (805) 968-6787
Email: kezal@toyon.com
Business Contact
Name: Marcella Lindbery
Title: Director of Finance and Contracts
Phone: (805) 968-6787
Email: mlindbery@toyon.com
Research Institution
N/A
Abstract
Toyon(R) proposes to develop a system for optimized resource allocation of networked sensors that will dynamically task sensors to support data fusion for improved surveillance, detection, tracking and discrimination of time-critical ballistic targets. We treat the problem as a closed-loop feedback system where a fusion-aided continuous identification (ID) process works with a dynamic sensor tasking (DST) module to maximize the information contained in the track database. The amount of information is quantified using an information-theoretic definition of the expected entropy in the track database given a candidate sensor schedule. The domain of sensor tasks involves a range of different sensor modes/waveforms so that the fusion and tracking module may best be serviced for different values of the expected signal-to-interference ratio, resolution, background clutter, drag coefficient, object classification and radar cross-section. The networked sensors need not be co-located. In Phase I, Toyon will develop radar, EO/IR and Ladar sensor models for our SLAMEM(R) simulation. We will then implement the DST module to control the new sensor models and evaluate the resulting performance. In Phase II, Toyon will improve the algorithm and the fidelity of the sensor models and will demonstrate the operation of the algorithm in real time for a scenario approved by the MDA and will develop hardware-in-the-loop simulation capability.

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