Enhanced Detection of Hidden Targets Using Multi-Discriminant Ladar

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA8651-08-C-0148
Agency Tracking Number: F071-156-2887
Amount: $749,246.00
Phase: Phase II
Program: SBIR
Awards Year: 2008
Solicitation Year: 2007
Solicitation Topic Code: AF071-156
Solicitation Number: 2007.1
Small Business Information
1775 Mentor Avenue, Suite 302, Cincinnati, OH, 45212
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Tom Sharp
 (513) 631-0579
Business Contact
 Tom Sharp
Title: Principal
Phone: (513) 631-0579
Email: tsharp@sdltd.com
Research Institution
To achieve the optimal detection and classification of hidden targets, a tightly linked sensor and algorithm design effort will be required. The Phase II work described here focuses on using data from an existing Ladar sensor to explore how high-dimensional spatial, spectral and polarimetric data can be used to detect and classify hidden targets. The general approach will be to apply specific dimensionality reduction techniques to experimental data to map the data into a lower dimension feature space. A point-surface invariant metric technique will be used to compare the identified features to a set of target CAD models. The statistical properties of the resulting classification will be examined in terms of detectability, separability, and robustness to noise. The following dimensionality reduction techniques will be explored: Diffusion Mapping and ISOMAP.

* Information listed above is at the time of submission. *

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