Performance evaluation of fuzzy-based fusion rules for tracking applications

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 generalized data association for targets' tracking; (2) Alarms identification and prioritization 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.