AESA-based RADAR Performance in Complex Sensor Environments

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N68335-10-C-0140
Agency Tracking Number: N062-123-0651a
Amount: $1,499,990.00
Phase: Phase II
Program: SBIR
Awards Year: 2010
Solicitation Year: 2006
Solicitation Topic Code: N06-123
Solicitation Number: 2006.2
Small Business Information
P.O. Box 238, Wayne, PA, -
DUNS: 946893658
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Joseph Schanne
 Senior Systems Engineer
 (610) 581-7940
Business Contact
 Joseph Teti
Title: Vice President
Phone: (610) 581-7940
Research Institution
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.

* Information listed above is at the time of submission. *

Agency Micro-sites

SBA logo
Department of Agriculture logo
Department of Commerce logo
Department of Defense logo
Department of Education logo
Department of Energy logo
Department of Health and Human Services logo
Department of Homeland Security logo
Department of Transportation logo
Environmental Protection Agency logo
National Aeronautics and Space Administration logo
National Science Foundation logo
US Flag An Official Website of the United States Government