YOLO-RD: A lightweight object detection network for range doppler radar images

Abstract

Under the condition of limited memory and computing power of radar aircraft equipment, large-scale object detection network based deep learning can not be deployed. Based on the darknet framework, Our paper proposes a lightweight object detection network for range doppler(RD) radar images: YOLO-RD, and builds a lightweight RD dataset: Mini-RD, for efficient network training. Firstly, YOLO-RD extracts features from the input image through a series of small convolutional. Secondly, the dense block connection module is used to design the backbone extraction network. Finally, the prediction layer is combined with multi-scale features for prediction. Experiments show that YOLO-RD has achieved good results on the mini-RD dataset with a smaller memory budget, with a detection accuracy of 97.54%.