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Performance evaluation of fuzzy-based fusion rules for tracking applications
Author(s) -
Albena Tchamova,
Jean Dezert
Publication year - 2015
Publication title -
hal (le centre pour la communication scientifique directe)
Language(s) - English
DOI - 10.5281/zenodo.22959
Subject(s) - fuzzy logic , fusion , tracking (education) , computer science , artificial intelligence , data mining , psychology , philosophy , linguistics , pedagogy
p>The objective of this paper is to present and to evaluate the performance of particularnbsp;fusion rules based on fuzzy T-Conorm/T-Norm operators for two tracking applications:nbsp;(1) Tracking object#39;s type changes, supporting the process of objects#39; identi cationnbsp;(e.g. ghter against cargo, friendly aircraft against hostile ones), which, consequentlynbsp;is essential for improving the quality of generalized data association for targets#39; track-nbsp;ing; (2) Alarms identi cation and prioritization in terms of degree of danger relatingnbsp;to a set of a priori de ned, out of the ordinary dangerous directions. The aim is tonbsp;present and demonstrate the ability of these rules to assure coherent and stable waynbsp;for identi cation and to improve decision-making process in a temporal way. A comparison with performance of Dezert-Smarandache Theory based Proportional Conflictnbsp;Redistribution rule no.5 and Dempster#39;s rule is also provided./p

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