SBIR/STTR Research Award

AESA-based RADAR Performance in Complex Sensor Environments

Award identifier 01fae1fad306275cb3960a192bee83b7aa46cdbad687bf75f8f53092ac76ce2fAwarding agency Department of Defense · Navy

Award amount

$1,499,990

Program and phase

SBIR · Phase II

Award year

2010

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Award details

Awarding agency
Department of Defense
Branch
Navy
Recipient company
Lambda Science, Inc.
Proposal award date
2010-02-09
Contract end date
2012-08-09
UEI
Q7G1NJBT1MW4
Solicitation number
2006.2
Topic code
N06-123

Research abstract

Many current United States Navy (USN) OPSIT/TACSIT scenarios comprise demanding dynamic environments for airborne sensors. The ability to task or mode interleave with adaptive scheduling is essential to achieving desired sensor/mission effectiveness. Both active electronically scanned array (AESA) and conventional mechanically scanned antenna (MSA) airborne multi-mode radar systems will require energy timeline resource management to realize their full performance capabilities. Real-time adaptive optimization of AESA control and scheduling over the implicitly large number of degrees of freedom is computationally impractical without sufficient constraints. In contrast, non-adaptive legacy resource management approaches rely exclusively on rule-based constrained methodologies that relax computational concerns, but significantly under utilize radar energy timeline resources. LSI proposes to extend the work currently being performed under our N06-123 effort that is building a modular framework to develop and evaluate sensor resource management (RM) concepts. We will also leverage the results of our recently completed N05-006 effort entitled “Radar Detection and Discrimination of Small Maritime Targets at High Altitude and Grazing Angle that examined simultaneous multi-target tracking and discrimination (MTT&D) through the inclusion of target features within an interactive multiple model/multiple hypothesis tracking (IMM/MHT) framework [1]. The connection between the RM and MTT&D lies in the desire to adaptively control sensor revisit and dwell time as needed, to maintain desired track quality and target discrimination. LSI will incorporate a MTT&D functional understanding and the associated performance attributes in the RM through the use of metadata. The overall proposed effort to develop and evaluate hybrid rule-based constrained optimization techniques for real-time adaptive optimization of airborne AESA and MSA control/scheduling involves many technical areas that are applicable to specific USN AESA radar sensors planned for the BAMS and VT-UAV platforms.

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.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

52 SBIR/STTR records share this UEI (2004–2024). Reported award amounts total $30,787,811. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Defense

Agency intelligence

Department of Defense

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