Advanced Algorithms for Exploitation of Space-Based Imagery

Award Information
Agency:
Department of Defense
Branch
Air Force
Amount:
$99,975.00
Award Year:
2005
Program:
SBIR
Phase:
Phase I
Contract:
FA8718-05-C-0041
Agency Tracking Number:
F051-014-1883
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
PHYSICAL SCIENCES, INC.
20 New England Business Center, Andover, MA, 01810
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
073800062
Principal Investigator:
Christopher Gittins
Principal Research Scientist
(978) 689-0003
gittins@psicorp.com
Business Contact:
B. Green
President, PSI R&D Operations
(978) 689-0003
green@psicorp.com
Research Institution:
n/a
Abstract
Physical Sciences Inc. and its subcontractor, SAIC-Boulder, propose to implement and evaluate two novel pattern recognition methods to mitigate cluster noise and enhance the contrast between targets and backgrounds in an automatic target recognition (ATR) applications. The proposed methods are relevant to subpixel target detection using hyperspectral data and are compatible with real-time implementation on airborne and spaceborne operating platforms. Our approach is to integrate a statistically-robust blind source separation algorithm for spectral signature recognition with a Bayesian Evidential Reasoning framework to enable context-based false alarm mitigation. The Bayes net will be used to reduce false rate by evaluating the spectral characteristics of the region surrounding the potential target detect. The proposed spectral pattern recognition approach is robust with respect to the form of clutter noise in the data, i.e., non-Gaussian noise statistics, and will enable modeling of Receiver Operating Characteristic (ROC) curves for any user-specified clutter noise distribution. The Phase I program will involve benchmark testing of the proposed methods using real and synthetic data sets and will enable recommendation of an ATR approach to be implemented in hardware in Phase II.

* information listed above is at the time of submission.

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