The traditional runway intrusion alarm equipment has the problems of low automation level and high cost of installation and maintenance. In this paper, the airport scene image information is obtained through the airport video system, and YOLOv5 is used to detect the airport scene aircraft. A lightweight network ShuffleNetv2 is used to optimize the DeepSORT algorithm to track the airfield aircraft. Through the monocular video acquisition system, the coordinate transformation and ranging model is established to accurately measure the distance between the airport aircraft and the runway midline. According to the ground protection zone, runway intrusion alarms can be realized by setting an appropriate threshold. The experimental results show that the average processing time of the optimized model is reduced by 2564%, the average ranging errors of aircraft 11, 18 and 43 cm from the runway center line in the simulated environment are 002, 001 and 001 cm, respectively, and the accuracy of runway intrusion alarm is 95.86%. The model has good realtime performance and high accuracy. This method can effectively prevent the occurrence of runway intrusion events.