FLIR & MMW Algorithms to Detect and Classify Stationary Targets

Award Information
Agency:
Department of Defense
Branch
Army
Amount:
$599,915.00
Award Year:
1995
Program:
SBIR
Phase:
Phase II
Contract:
n/a
Award Id:
20666
Agency Tracking Number:
20666
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
P.o. Box 560788, Orlando, FL, 32856
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
n/a
Principal Investigator:
Alexander Akerman Iii
(407) 857-3213
Business Contact:
() -
Research Institute:
n/a
Abstract
Six multisensor (FLIR/MMW) data bases will be accessed to include all those at CNVEOD including the VISION 1 and subsequent field tests, particularly those involving the RIMS and BWI MMW radars, along with the IIDAS and SAIRS FLIRS. Data from other government agencies will include that in TABILS and at HDL, MICOM, and AATD. A Phase II plan will be produced for training and testing three ATR algorithms not heretofore considered for tank-mounted applications but proven in related contexts: 1. An adaptive Bayesian statistical classifier, which in its operational implementation would be continually retrained upon the actual ground clutter within which the tank is operating. 2. A "genetic" algorithm, which uses the same feature sets as #1, but evolves a different polynomial discriminant function. Both the "genetic" and "adaptive" classifier algorithms are under development for the LONGBOW MMW radar by Systems Dynamics, who would be subcontracted to I-MATH for this SBIR. 3. Geometric hashing algorithms, which I-MATH has recently developed using a CNVEOD-provided FLIR imagery under a Phase II Air Force SBIR. Such algorithms provide a robust mechanism for multisensor fusion as well, since each feature is indexed by its geometric position. This greatly facilitates the incorporation of MMW range (z) profiles as a third coordinate to FLIR (x,y) has points.

* information listed above is at the time of submission.

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