A relationship between eye movement patterns and performance in a precognitive tracking task

Abstract

Eye movements made by various subjects in the performance of a precognitive tracking task are studied. The tracking task persented by an antiaircraft artillery (AAA) simulator has an input forcing function represented by a deterministic aircraft fly-by. The performance of subjects is ranked by two metrics. Good, mediocre, and poor trackers are selected for analysis based on performance during the difficult segment of the tracking task and over replications. Using phase planes to characterize both the eye movement patterns and the displayed error signal, a simple metric is developed to study these patterns. Two characterizations of eye movement strategies are defined and quantified. Using these two types of eye strategies, two conclusions are obtained about good, mediocre, and poor trackers. First, the eye tracker who used a fixed strategy will consistently perform better. Secondly, the best fixed strategy is defined as a Crosshair Fixator