Next Generation Sensor Resource Management for Persistent and Responsive Situational Awareness

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA9453-09-M-0063
Agency Tracking Number: F083-185-0533
Amount: $99,942.00
Phase: Phase I
Program: SBIR
Awards Year: 2009
Solitcitation Year: 2008
Solitcitation Topic Code: AF083-185
Solitcitation Number: 2008.3
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
 Peter Shea
 Dir of New Product Develo
 (315) 732-7385
 CBeebout@RadiationAssuredDevices.co
Business Contact
 Milissa Benincasa
Title: Dir of New Product Develo
Phone: (315) 732-7385
Email: CBeebout@RadiationAssuredDevices.co
Research Institution
N/A
Abstract
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.

* information listed above is at the time of submission.

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