Tracking applications with fuzzy-based fusion rules

Abstract

The objective of this paper is to present and evaluate the performance of a particular fusion rule based on fuzzy T-Conorm/T-Norm operators for two tracking applications: (1) Tracking Object's Type Changes, supporting the process of identification, (e.g. friendly aircraft against hostile ones, fighter against cargo) and consequently for improving the quality of generalized data association; (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 TCN rule to assure coherent and stable way for identification and to improve decision-making process in temporal way. A comparison with performance of DSmT based PCR5 fusion rule and Dempster's rule is also provided.

Performance evaluation of fuzzy-based fusion rules for tracking applications

“…The goal is to improve the process of data fusion and to successfully finalize the decision-making procedures in both described above surveillance cases. The work is based on preliminary research in Smarandache, 2004-2009;Tchamova and Dezert, 2013). The basics of Proportional Conflict Redistribution rule no.5 (PCR5), defined within DSmT are recalled in Section II.…”