The drone platform has small memory and limited computing resources.Aiming at the problems of complex network structure and slow detection speed of classical detection methods, a real-time detection method based on lightweight is proposed. Firstly, the lightweight model MobileNetv3 replaces CSPDarknet53 as the backbone network and the effective channel attention mechanism is fused to reduce the memory occupation of the model. Secondly, the residual structure fusion module RFM is introduced to enhance the feature extraction capability of the network. To further improve the generalization ability of obstacle detection and the convergence speed of the algorithm, the Control Distance-IOU loss function is replaced by the CIOU loss function for network training.The experimental results show that memory occupation of the improved model is reduced by 80% to only 39.5M and the FPS is improved by 168% to 49.21 frames/s under the same basic detection effect as the original model.