2004 IEEE Radar Conference

Innovative Radar Technologies - Expanding System Capabilities

 
 
 April 26-29, 2004 Wyndham Philadelphia at Franklin Plaza Philadelphia, Pennsylvania
 
 
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Session 6B.5
Belief Fusion, Pignistic Probabilities, and Information Content in Fusing Tracking Attributes

John J. Sudano - LMC

Wed, 28 April 2004, 10:20 AM - 12:00 PM


Abstract

Abstract- In the design of information fusion systems, the reduction of computational complexity is a key design parameter for real-time implementations. One way to simplify the computations is to decompose the system into subsystems of non-correlated informational components, such as a qualitative informational component, a quantitative informational component, and a complement informational component. A probability information content (PIC) variable [6] assigns an information content value to any set of system or sub-system probability distributions. The PIC variable is the normalized entropy computed from the probability distribution. This article derives a PIC variable for a subsystem represented by the complement probabilities. This article also derives a relationship between the PIC variable of sub-system components and the system informational PIC variable. A series of pignistic probability transforms are presented that estimate the probability for any belief data set. The Generalized Belief Fusion method of combining independent multi-source beliefs is presented.

Bio

Dr. John J. Sudano - LMC

Dr. John Sudano is presently employed as a principal member of the engineering staff with Lockheed Martin, Moorestown, NJ, where he is doing research in the automated integration of dissimilar sensor information for identification, for robust tracking, the representation of true position and velocity tracking errors and precise gravitational representation for missile tracking. Some of his other research interests include tracking and information discrimination in hostile environments, automated identification methodologies, statistical signal processing, and error estimation in information-fusion processes. Dr. John Sudano received a Ph. D. degree from New York University, an M.S. from Michigan State University, and a B.S. from Fairleigh Dickinson University, all in Physics. He presently has three patents with one pending and has published 38 technical articles. He has been a member of the IEEE for 25 years. Presently, he is the chair of the executive committee of the IEEE Philadelphia section and vice-chairperson of the Philadelphia section of the Aerospace and Electronic System Society.

 
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