Title: Performance evaluation of fuzzy-based fusion rules for tracking applications

Authors: Albena Tchamova; Jean Dezert

Addresses: Institute of Information and Communication Technology, Bulgarian Academy of Science, Bulgaria ' The French Aerospace Lab, Chemin de la Hunière, F-91761 Palaiseau, France

Abstract: The objective of this paper is to present and to evaluate the performance of particular fusion rules based on fuzzy T-Conorm/T-Norm operators for two tracking applications: 1) tracking object's type changes, supporting the process of objects' identification (e.g., fighter against cargo, friendly aircraft against hostile ones), which, consequently is essential for improving the quality of generalised data association for targets' tracking; 2) alarms' identification and prioritisation in terms of degree of danger relating to a set of a priori defined, out of the ordinary dangerous directions. The aim is to present and demonstrate the ability of these rules to assure coherent and stable way for identification and to improve decision-making process in a temporal way. A comparison with performance of Dezert-Smarandache Theory-based Proportional Conflict Redistribution rule no. 5 and Dempster's rule is also provided.

Keywords: object types; object identification; alarm classification; data fusion; Dezert-Smarandache Theory; DSmT; fuzzy-based fusion rules; TCN rules; PCR5 fusion rule; Dempster's rule; performance evaluation; fuzzy logic; target tracking; decision making.

DOI: 10.1504/IJRIS.2014.066251

International Journal of Reasoning-based Intelligent Systems, 2014 Vol.6 No.3/4, pp.126 - 135

Received: 08 May 2021
Accepted: 12 May 2021

Published online: 09 Dec 2014 *

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