Improved Information Extraction

Award Information
Agency: Department of Defense
Branch: Defense Advanced Research Projects Agency
Contract: W31P4Q04CR027
Agency Tracking Number: 02SB2-0065
Amount: $284,233.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: N/A
Solicitation Number: N/A
Timeline
Solicitation Year: N/A
Award Year: 2003
Award Start Date (Proposal Award Date): N/A
Award End Date (Contract End Date): N/A
Small Business Information
5302 Rymney Lane, Burke, VA, 22015
DUNS: 008952009
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Raymond Fitzgerald
 Vice President
 (703) 978-4483
 fitzgerald@csssols.com
Business Contact
 J. McKisic
Title: President
Phone: (703) 323-8213
Email: mckisic@csssols.com
Research Institution
N/A
Abstract
Existing signal processing algorithms for remote sensing were typically derived, first, by formulating the problem in the context of one of the following: inverse theory (e.g. integral equations, integral transforms, deconvolution), singular valueddecomposition,filter theory, estimation theory, information theory, detection theory, or beamforming; and then, second, by deriving a solution thatmeets a single optimization criterion. For example, based on filter theory, the generalized sidelobe canceller selects the unbiased filterhaving minimum output power consistent with constraints. We discovered a new problem formulation that provides an optimum solution with additional degrees of freedom. For certain,specific choices of these additional degrees of freedom, the new solution reduces to known algorithms. For other choices, our approachprovides new algorithms with added capability that allows multiple processing objectives to be met optimally and simultaneously. We propose to demonstrate the feasibility of this new approach in an application of programmatic interest to DARPA,in particular, improved detection and classification in FTIR spectroscopy.

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

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