When the scale and viewing angle of flying targets such as aircraft change，Kernelized Correlation Filtering (KCF) algorithm may cause target tracking loss due to fixed tracking boundary and low filtering accuracy. To solve this problem，based on the KCF algorithm，a model updating strategy is added to improve the accuracy of the model，and the YOLOv5l detection network is used to achieve accurate estimation of the target scale. Finally，the experimental results on the constructed aircraft target dataset show that the improved KCF algorithm has improved the accuracy and success rate by 0.315 and 0.285 respectively in comparison with the original algorithm，and it has good tracking performance when the target scale and viewing angle change.