Abstract: A 4D aircraft track tracking algorithm based on cloud platform and eye movement fixation point data is proposed to track aircraft tracks in real time， detect and correct potential safety hazards in time， and reduce the occurrence of flight accidents. The 4D aircraft track tracking architecture is built with the help of cloud platform， which includes five levels of data acquisition， transmission， storage， processing and application services. Infrared cameras and sensors in the acquisition layer are used to collect pilot eye movement data and aircraft flight data. Using the transport layer， these data are transmitted wirelessly to the cloud storage area in the storage layer. In the data processing layer， the aircraft flight data with multiple information sources is integrated. In the application service layer， the trajectory information of the pilot’s fixation point is obtained through the operation of pupil positioning and fixation point calibration， and it is regarded as the important supplementary information of aircraft 4D track tracking. A 4D flight path prediction model of aircraft based on deep neural network is constructed. The integrated flight data of aircraft and the pilot’s gaze point trajectory information are taken as the input of the model， and the output result of the model is the 4D flight path prediction result of aircraft. Markov distance is used to compare the forecast results with the preset route， and the control parameters of the aircraft are adjusted according to the comparison results to realize the 4D track tracking. Experimental results show that this method can track aircraft 4D track accurately and has a good performance in differential flatness.

Key words: cloud platform, aircraft, data fusion, eye movement fixation point data, 4D track tracking, fixation point calibration