Advanced Sensor Data Fusion

Award Information
Agency:
Department of Defense
Branch
Missile Defense Agency
Amount:
$99,972.00
Award Year:
2007
Program:
STTR
Phase:
Phase I
Contract:
W9113M-07-C-0233
Award Id:
83272
Agency Tracking Number:
B074-004-0081
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
75 Aero Camino, Suite A, Goleta, CA, 93117
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
153927827
Principal Investigator:
GaryKey
Principal Investigator
(321) 277-8396
garykey@aol.com
Business Contact:
IvaHeins
Contracts Manager
(805) 685-6672
iheins@fti-net.com
Research Institute:
UNIV. OF FLORIDA
Roslyn Oleson
Office of Engineering Research
POB 116550, 339 Weil Hall
Gainesville, FL, 32611
(352) 392-9447
Nonprofit college or university
Abstract
Frontier Technology, Inc. (FTI) and its research partner, University of Florida (UF), propose to develop designs for innovative discrimination algorithms for fusion of sensor (feature) and contextual information, to provide enhanced acquisition, tracking, and discrimination of threat objects in a cluttered multi-target environment. We propose to analyze the performance of the envisioned technology to support: (a) Dynamic acquisition of target state data (e.g., motion, spectral, spatial cues) from sensor output, (b) Application of multiple classifiers to target/background radar or EO/IR and target state data to identify probable target type/track/location, (c) Adaptation of classifiers to track targets given nonergodic (statistically changing) inputs, (d) Execution on small, low-power on-board processing systems Adaptive pattern selection, key to successful sensor fusion in mission- and threat-specific scenarios, will utilize FTI's TNE pattern recognition paradigm and UF's Morphological Neural Nets (MNN). Phase I will extend and analyze FTI and UF's successful, DoD-sponsored R&D for dynamic pattern recognition to develop target detection algorithms for multiple radar or EO/IR sensor data, to detect and discriminate threats from manmade or naturally-occurring clutter. Phase II will develop and test prototype image processing software to incorporate multiple sensors of differing wavebands using obscured moving and stationary targets.

* information listed above is at the time of submission.

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