Nonadditive probability, finite-set statistics, and information fusion
- 19 November 2002
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 2, 1947-1952 vol.2
- https://doi.org/10.1109/cdc.1995.480631
Abstract
Information fusion is the name given to military expert-systems problems. In this paper we summarize recent work proposing a fully probabilistic theoretical unification for much of information fusion based on the theory of random sets. Our approach unifies detection, localization, classification, and prior knowledge with respect to these. It also unifies precise data together with imprecise data and propositional or vague/fuzzy evidence, as well as certain associated methodologies (e.g., fuzzy logic, rules). Underlying our approach is the discovery that classical single-sensor, single-target point-variate statistics can be directly generalized to a multisensor, multitarget statistics of finite-set variates. We describe "finite-set statistics" and its application to multisensor estimation using diverse data forms. We also point out relationships with current theoretical statistics.Keywords
This publication has 10 references indexed in Scilit:
- Unified nonparametric data fusionPublished by SPIE-Intl Soc Optical Eng ,1995
- Fundamentals of Uncertainty Calculi with Applications to Fuzzy InferencePublished by Springer Nature ,1995
- Random-set approach to data fusionPublished by SPIE-Intl Soc Optical Eng ,1994
- Limit Theorems for Unions of Random Closed SetsLecture Notes in Mathematics, 1993
- The transferable belief model and random setsInternational Journal of Intelligent Systems, 1992
- Uncertainty and Vagueness in Knowledge Based SystemsPublished by Springer Nature ,1991
- Statistics with Vague DataPublished by Springer Nature ,1987
- Tracking and classifying multiple targets withouta prioriidentificationIEEE Transactions on Automatic Control, 1986
- The Boolean model and random setsComputer Graphics and Image Processing, 1980
- On random sets and belief functionsJournal of Mathematical Analysis and Applications, 1978