AESA-based RADAR Performance in Complex Sensor Environments

Award Information
Agency:
Department of Defense
Branch
Navy
Amount:
$600,000.00
Award Year:
2008
Program:
SBIR
Phase:
Phase II
Contract:
N68335-08-C-0136
Award Id:
77030
Agency Tracking Number:
N062-123-0651
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
P.O. Box 238, Wayne, PA, 19087
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
946893658
Principal Investigator:
Joseph Schanne
Senior Systems Engineer
(610) 581-7940
jjschanne@lamsci.com
Business Contact:
Joseph Teti. Sr.
Vice President
(610) 581-7940
jteti@lamsci.com
Research Institution:
n/a
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. Furthermore, the programmable nature of many modern AESA based sensor architectures allows real-time modification of antenna pattern and waveform characteristics. 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. Recent real-time computer systems research in optimum scheduling in complex dynamic environments has produced computationally efficient approximate solutions that are attractive for use with rule-based constraints. LSI proposes to develop and evaluate hybrid rule-based constrained optimization techniques for real-time adaptive optimization of airborne AESA and MSA control and scheduling. These techniques will apply to airborne AESA and MSA radar systems of interest to the USN and address both air-to-air and air-to-ground operation.

* information listed above is at the time of submission.

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