NASA SBIR 2003 Solicitation

FORM B - PROPOSAL SUMMARY


PROPOSAL NUMBER:03-E3.04-8410 (For NASA Use Only - Chron: 034595)
SUBTOPIC TITLE:Geospatial Data Analysis Processing and Visualization Technologies
PROPOSAL TITLE:Data Reduction and Rapid Analysis of Hyperspectral Data Sets

SMALL BUSINESS CONCERN (Firm Name, Mail Address, City/State/Zip, Phone)
PERL Research, LLC
4800 Whitesburg Drive Suite 30-136
Huntsville ,AL 35802 - 1600
(256) 651 - 8169

PRINCIPAL INVESTIGATOR/PROJECT MANAGER (Name, E-mail, Mail Address, City/State/Zip, Phone)
Paul    Cox
paul@perlresearch.com
4800 Whitesburg Drive Suite 30-136
Huntsville ,AL  35802 -1600
(256) 651 - 8169
U.S. Citizen or Legal Resident: Yes

TECHNICAL ABSTRACT (LIMIT 200 WORDS)
Hyperspectral sensors offer great opportunities for increasingly sensitive automated target recognition (ATR) systems though a common problem is the lack of sufficient training data. Also, the inherent high dimensionality of hyperspectral signatures requires the design of a hyperspectral ATR to have a large number of training samples. This is due to the fact that the number of training samples required is directly related to the dimensionality of the classifier. In order to avoid this problem, the hyperspectral datasets must be preprocessed, thereby reducing the dimensionality to an acceptable level. Other challenges include uncertainty associated with measurements and missing/sparse data sets. To meet these challenges, the PERL Research and Mississippi State University will develop a unique ATR system for data reduction and rapid analysis of hyperspectral data. Our proposed approach is based on the integration of two concepts: localized discriminant bases and support vector machines. Our proposed ATR system will be able to rapidly cope with limited/sparse training data while producing optimal target recognition accuracies. Furthermore, the ATR will provide a unique capability for easy integration with various sensors and other ATR systems.

POTENTIAL NASA COMMERCIAL APPLICATIONS (LIMIT 150 WORDS)
The proposed ATR Fusion system could provide critical improvements to the target detection capabilities of the Invasive Species Forecasting System.

POTENTIAL NON-NASA COMMERCIAL APPLICATIONS (LIMIT 150 WORDS)
Land Resource Management; identification and assessment of environmental conditions and hazards, process data sets for unmanned aerial vehicles (UAVs) and reconnaissance planes and satellites both commercial and military