Jet noise has become one major concern for aircraft engine design in recent decades. The problem is to identify the near-field (NF) structures that produce far-field (FF) noise in order to improve noise control and reduction strategies. An algorithm has been developed to identify the events that are captured by several signals simultaneously in both NF and FF. In this paper, we attempt to improve the reliability of a previously devised algorithm that looks for main contributors to NF-FF correlations.1;2 We focus on one set of experimental data from Mach 0.6 jet. It consists of 10kHz TRPIV measurement and pressure sampling in both NF and FF. Q criterion signals at different NF locations are compared with FF Microphone signals inside the cone of coherence. The potential events extracted are interpretted as part of the large coherent structures that correlate with the FF. In the time-frequency domain, the events are short wave packets, distorted by ambient perturbations. The algorithm is tested by synthetic signals which are composed of Morlet wave packets and background noise. The NF localization and time sequencing of these potential event clusters are compared to another two lists of event candidates.3,1,2.