Truth Quest: Enabling Operational/Exercise Data

Award Information
Agency:
Department of Defense
Branch
Air Force
Amount:
$615,130.00
Award Year:
2003
Program:
SBIR
Phase:
Phase II
Contract:
F33615-03-C-1432
Award Id:
57720
Agency Tracking Number:
021SN-0056
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
910 Technology Blvd. Suite A, P. O. Box 1563, Bozeman, MT, 59771
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
049451706
Principal Investigator:
Robert Crabtree
Director of Science
(406) 556-9880
crabtree@yellowstoneresearch.org
Business Contact:
Ron Cooper
President
(406) 556-9880
roncooper@hyperspectives.net
Research Institution:
n/a
Abstract
The Phase II project will address enhancing ATR by developing techniques that use single and fused remotely sensed data sets to precisely characterize terrain environments, areas of potential trafficability, and areas of EOC clutter that can be ignored bythe ATR algorithms. These precision EOC identification and clutter-removal processes can be utilized as (1) a pre-ATR (terrain/ target potential or possible area) assessment and/or (2) a post-ATR refinement (change detection) process. The toolbox willconsist of multiple processing and analysis pathways suited to a variety a data sets and conditions. Data analysis will rely upon the use of spectral and spatial analysis. The analysis includes single image classification, fused classification, andsingle data type and fused data spectral/backscatter and spatial analysis techniques The process precisely discriminates and classifies fine scale landscape features. The use of spatially explicit techniques for classification and spatial patternidentification assists in (1) assess classification uncertainty; (2) quantification of expected rates for false negatives and false positives; (3) provides a probabilistic assessment of landscape features for both target and non-target classes. Theresult is a process to measure landscape features (characterize terrain) with a high level of precision and accuracy.

* information listed above is at the time of submission.

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