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T5 An Introduction to Finite-Set Statistics for Information Fusion

Length: 3 hours

Intended Audience: Those interested in learning more about and how to use finite-set statistics.

Description: Finite-set statistics is a theoretically unified mathematical machine for solving information fusion problems, based on random set theory. First systematically described in Statistical Multisource-Multitarget Information Fusion (Artech, 2007), it has attracted the interest of dozens of research groups in at least 19 nations, resulting in well over a thousand publications. Advances in Statistical Multisource-Multitarget Information Fusion (Artech, 2014) systematically described the most intriguing aspects of this research, including algorithms that outperform conventional approaches. Previous tutorials have focused on applications of random set information fusion. This is the first systematic tutorial treatment of finite-set statistics itself. Topics: (1) Introduction. (2) Why should you care? (an overview of finite set statistics-based practical advances). (3) Basic single-sensor, single-target filtering theory. (4) Basic unified, Bayes-optimal “hard + soft” fusion. (5) Random finite sets (RFS’s) and correct phenomenological modeling of multiarget systems. (6) Labeled RFS’s and track continuity. (7) Multitarget differential calculus. (8) “Turn the crank” formulas of multitarget calculus. (9) Fundamental multitarget statistical descriptors. (10) Summary statistical descriptors. (11) Important RFS’s. (12) RFS multitarget modeling. (13) Multitarget Bayes filter and multitarget Bayes optimality. (14) Approximate RFS filters and the finite set statistics approximation methodology. (15) Multitarget metrology (optimal sub-pattern assignment (OSPA) metric, information-theoretic functionals).

Prerequisites: General familiarity with information fusion.

Presenter: Ronald Mahler

Ronald Mahler, founder and CEO of Random Sets, LLC, has a Ph.D. in mathematics and a B.E.E. in Electrical Engineering. He is author or coauthor of over a hundred publications in random set information fusion, including three books and nearly two dozen journal papers. Two of these are the most-cited and fourth-most-cited papers published in IEEE Trans. Aerospace & Electronic Sys. over the last decade. He has been invited to speak at numerous universities, U.S. Department of Defense Laboratories, and conferences, including a keynote address at FUSION2004. He is recipient of the 2007 Mignogna Data Fusion Award, the 2005 IEEE AESS Mimno Award, and the 2007 IEEE AESS Carlton Award. He has been listed in Who’s Who in America and Who’s Who in the World since 2010. He has previously given well-attended tutorials at the 2008, 2009, 2010, 2012, and 2015 FUSION conferences.

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