Adaptive Data Fusion for Maritime Surveillance

Period of Performance: 10/19/1998 - 08/18/1999

$70K

Phase 1 SBIR

Recipient Firm

Orincon Corp.
4770 Eastgate Mall
San Diego, CA 92121
Principal Investigator

Research Topics

Abstract

The 21st century Navy will need complete awareness of the surface and subsurface situations across a wide area of interest, in spite of the constraints of reduced budgets and manning levels, and the need for closer collaboration with other forces. To meet these new challenges, the fleet must rely on technology innovation, leveraging of existing programs, and consolidation of common functions across platforms. ORINCON's proposed research and development concentrates on the surveillance problem of high target density in a cluttered maritime environment. Our effort focuses on robust data fusion for ISR through algorithmic adaptation. Our goals are to incorporate adaptive control of the fusion process in the baseline Contact Management/Common Module architecture; to develop a fuzzy controller to select fusion algorithms based on changing problem context; and to demonstrate the resulting context-dependent dynamic adaptation of the fusion system. The immediate benefits will include improved tracking and classification performance, increased modularity and portability between platforms, and expanded interfaces to additional sensors. In a broader context, the Navy will experience payoffs in terms of leveraging of existing technology and improved performance that is widely applicable to surface-, subsurface- and land-based systems.