Probabilistic Evidential Reasoning for Collecting Signals Intelligence Data

Award Information
Agency: Department of Defense
Branch: Army
Contract: W15P7T-09-C-S002
Agency Tracking Number: A072-106-1143
Amount: $1,203,040.00
Phase: Phase II
Program: SBIR
Awards Year: 2009
Solicitation Year: 2007
Solicitation Topic Code: A07-106
Solicitation Number: 2007.2
Small Business Information
Management Sciences, Inc.
6022 Constitution Avenue NE, Albuquerque, NM, 87110
DUNS: 094142122
HUBZone Owned: N
Woman Owned: Y
Socially and Economically Disadvantaged: N
Principal Investigator
 Carl Stern
 Senior Research Scientist
 (505) 255-8611
 carl_stern@mgtsciences.com
Business Contact
 Marlene Blemel
Title: President
Phone: (505) 255-8611
Email: kay_blemel@mgtsciences.com
Research Institution
N/A
Abstract
The goal of this project is to develop a scalable software platform for SigInt collection management and data fusion. This platform will help provide SigInt analysts and users with effective access to the right information at the right time while helping to reduce information overload. The platform is designed to support a cognitive style of information processing and data fusion. The computational methods are cognitive in the sense that they implement a logico-mathematical process that is flexible, context sensitive, and hypothesis-driven, emulating the way in which human experts assimilate and interpret arriving data, progressively transforming data into information and understanding, while gracefully adapting or revising old hypotheses as needed based on newly detected events and conditions. The platform uses information framing and multi-layer fusion to organize collected information, to group, filter, and fuse signals intelligence data, and to organize the presentation of data to users and analysts. The framing and fusion algorithms provided by this toolset will be used to support the work and enhance the effectiveness of SIGINT analysts as they assess the relationships between detection events to discover patterns and trends, improving the accuracy and efficiency of analyst detection, identification, and geo-location of emerging threats.

* information listed above is at the time of submission.

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