For infrared multi-scale target detection,a lightweight detection network based on single-stage receptive field enhancement is proposed.The detection network uses the simplified MobileNet V2 as the backbone network.In combination with atrous convolution and spatial attention mechanism,a single-stage receptive field enhancement module is designed to expand the receptive field range of the single-stage feature map and enhance the correlation between adjacent pixels.In order to improve the back propagation efficiency of the model and balance the positive and negative samples,the adaptive training sample selection method is adopted.Finally,a lightweight detection algorithm with the model size of only 1.6×32 Mibit and the floating-point operation of only 5.63GFLOPS is obtained.On the constructed MTS-UAV data set,the mAP reaches 89.6%,and the FPS reaches 105 frame/s on RTX2080Ti.