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>