To solve the problems of low detection accuracy and slow detection speed of small targets in the task of detecting the brightness of the runway edge lights in the airport, a method for detecting the brightness of the runway edge lights based on improved RetinaNet is proposed in this paper. Based on the RetinaNet, the inverted residual structure and depth separable convolution are introduced to improve the feature extraction ability and detection speed of the network. The K-means clustering algorithm is used to optimize the size of the anchor box of the target sample to improve the detection accuracy of the network. The experimental results show that compared with the original method, the performance of the method is significantly improved, with the average detection accuracy of 97.2% and detection speed of 25.9 frame/s.