SBIR/STTR Research Award

Unified Control-Theoretic Bayesian Multi-Sensor Multi-Target Sensor Resource Management

Award identifier a8cf47049088c9d842201779278f477804ce7e442931a2ecd5ba6cf6e61baa9dAwarding agency Department of Defense · Air Force

Award amount

$99,928

Program and phase

SBIR · Phase I

Award year

2003

Explore This Research Award in CaptureIQ

Research the technology, evaluate the recipient and agency, identify related opportunities, and explore potential follow-on work with CaptureIQ.

Award details

Awarding agency
Department of Defense
Branch
Air Force
Recipient company
SCIENTIFIC SYSTEMS COMPANY, INC.
Proposal award date
Not reported
Contract end date
Not reported
UEI
C12TQVKF5413
Solicitation number
Not reported
Topic code
Not reported

Research abstract

Adaptive real time Sensor resource management (SRM) is inherentlya problem in optimal nonlinear control theory, in which datacollection/interpretation and sensor coordination should betightly connected by a control-theoretic feedback loop thatallows the results of existing collections and anticipated futuresensing and target conditions to influence the choice of futurecollections. Scientific Systems Company, Inc. (SSCI) and itssubcontractor Lockheed Martin Tactical Systems (LMTS) propose theimplementation of a foundational approach to control-theoreticSRM, and will develop a systematic control-theoretic foundationand calculus for multisensor-multitarget sensor management, aswell as techniques for rendering that foundation computationallytractable. The major objectives of Phase I will be to: (1)develop the necessary theoretical extensions; (2) developscalable and tractable computational approximations; (3)implement concept-feasibility prototype algorithms; (4) test thisalgorithm in simulated, reduced-complexity scenarios involving afew sensors on a single platform operating against a small numberof targets; and (5) develop a detailed plan for further analysisand implementation in a Phase II effort.Phase II will emphasize the development of more sophisticatedprototype versions of the integrated data fusion and sensorresource management algorithms developed in Phase I. Commercialapplications of the approach will also be investigated by SSCIand LMTS during Phase I and fully developed during Phase II. The technology developed in this proposal has specificapplications to military and commercial applications. Theseinclude developers and users of agile, multi-mode airborne radarsystems, both tactical and ISR aircraft. Tactical systems canutilize adaptive sensor control to reduce pilot workload whileincreasing situational awareness. Commercial applications includenon-military surveillance systems such as monitoring of airports,border crossings, power plants, and other sensitive publicfacilities.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Research funding history

464 SBIR/STTR records share this UEI (1983–2025). Reported award amounts total $186,567,405. Reported amounts are not federal obligations.

Phases: Phase I, Phase II, Phase II – Direct to Phase II

Agencies: Department of Defense, National Aeronautics and Space Administration, National Science Foundation, Department of Energy, Department of Health and Human Services, Department of Homeland Security

Agency intelligence

Department of Defense

Back to SBIR/STTR Research Awards

Don't take our word for it. Ask AI about RFPCapture.

See what leading AI assistants have to say about RFPCapture and CaptureIQ.

Gemini opens without a prefilled question. The question is copied to your clipboard when the button works. You can also copy it here:

What is RFPCapture.com and its CaptureIQ platform from Smart Logic AI? How does it help federal contractors discover opportunities, evaluate bid/no-bid decisions, research government contracts, and prepare proposals? How does it compare with other federal capture platforms? Use independent sources where available.