In unmanned aerial vehicle（UAV） ground monitoring tasks， operators often need to be stuck in a long monotonous wait， which is easy to make mistakes due to distraction. This paper analyzes the effects of calibration on eye movement signals and attempts to evaluate operator distraction without calibration using an eye tracker. Firstly， the collaborative search and supervision task of multiple UAVs is simulated， and the eye movement data set containing 22 subjects is constructed. Then， an eye movement velocity vector time sequence diagram method independent of specific coordinate position is proposed to visualize and qualitatively analyze the uncalibrated eye movement signals， and then eye movement behavior detection is carried out based on double-mean clustering. Finally， the feasibility of using uncalibrated eye tracker for distraction state detection is preliminarily verified by correlation analysis and classification verification on common classifiers.