An Information-Theoretic Approach to Sensor Resource Management for Situational Assessment

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA8750-05-C-0070
Agency Tracking Number: F041-102-2980
Amount: $750,000.00
Phase: Phase II
Program: SBIR
Awards Year: 2005
Solicitation Year: 2004
Solicitation Topic Code: AF04-102
Solicitation Number: 2004.1
Small Business Information
Suite A, 75 Aero Camino, Goleta, CA, 93117
DUNS: 054672662
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Mark Meloon
 Senior Analyst
 (805) 968-6787
Business Contact
 Marcella Lindbery
Title: Director of Finance and C
Phone: (805) 968-6787
Research Institution
Toyon Research Corporation proposes to continue our research on Sensor Resource Management (SRM) designed to improve Situational Assessment (SA). Our approach is to cast SRM in the form of an optimization problem with an objective function featuring Shannon entropy. SA is defined as estimating entity states based on inferred relations among entities, therefore, reducing the entropy of the SA database will drive the system to detect, identify, classify, and track aggregates of vehicles. In Phase I, we have focused on the problem of identifying air defense systems to demonstrate how we can achieve a high degree of classification performance with relatively few sensor measurements. In Phase II, we will develop sophisticated SRM logic to better emulate the SA fusion process, improve the association and classification algorithms in the SA module, use a wider range of sensor operations, and use dynamic analysis of known entities to dictate the searching designed to identify new relations and detect tactically significant events. The resulting system will be demonstrated against significantly more complicated test problems featuring a variety of aggregate types and tactics occurring over multiple areas.

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

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