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Next Generation Sensor Resource Management for Persistent and Responsive…

Award Information

Department of Defense
Air Force
Award ID:
Program Year/Program:
2009 / SBIR
Agency Tracking Number:
Solicitation Year:
Solicitation Topic Code:
Solicitation Number:
Small Business Information
Black River Systems Company, Inc.
162 Genesee Street Utica, NY -
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Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
Phase 1
Fiscal Year: 2009
Title: Next Generation Sensor Resource Management for Persistent and Responsive Situational Awareness
Agency / Branch: DOD / USAF
Contract: FA9453-09-M-0063
Award Amount: $99,942.00


Todays battlefield environment contains a large number of sensors onboard multiple platforms. In an attempt to maximize sensor performance, todays sensors employ rudimentary or in some cases inflexible sensor tasking schemes which are highly tuned approaches that are not very robust to changes in the mission, environmental conditions, heterogeneous sensors, and different system architectures. The general missions of interest include search, detect, track, and classification and as a result there is a need to manage sensors to not only address the needs of the individual mission, but also to consider potential overlap between the different mission areas. As the complexity of the problem space increases and new sensors become available, it is critical to have a sensor management scheme that is capable of incorporating new environmental knowledge, new sensors and different systems approaches with minimal impact on the overall system. The objective of this Phase I SBIR effort is to combine the Black River Systems Company sensor management testbed with Atmospheric and Environmental Research environmental impacts tools to provide optimal sensor tasking in a decentralized, distributed configuration that can save analysts time and money while providing overall improved predictive situational awareness. The focus of our Phase I effort will be to use reasonably mature and readily available technologies from our two companies to demonstrate the performance gain achievable when accounting for the dynamic environmental state at the time of sensor tasking. BENEFIT: Upon successful completion of our Phase I effort we will have demonstrated the ability to incorporate environmental models and predictions into a closed loop sensor management testbed. Using this capability we will perform a series of trade studies to understand the performance gains for different numbers and types of sensor platforms and sensor management configurations.

Principal Investigator:

Peter Shea
Dir of New Product Develo

Business Contact:

Milissa Benincasa
Dir of New Product Develo
Small Business Information at Submission:

162 Genesee Street Utica, NY 13502

EIN/Tax ID: 161515846
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No