To solve the problems of inadequate feature information,serious feature loss and low recognition accuracy in the process of infrared UAV target recognition,an infrared UAV target detection method based on YOLOv7 is proposed.By introducing the attention mechanism,the feature representation ability of the target region is enhanced and the spatial information content of the image is improved.The improved serial connection mode is used to connect the channel attention module to the spatial attention module.While combining the channel feature information with the spatial feature information,the improved structure reduces the negative impact of the channel attention on infrared image recognition,and can better realize the feature strengthening of the infrared target.The SIoU loss function based on angle vector regression is selected as the frame loss function,which further improves the convergence and detection accuracy of the model.The experimental results show that the reasoning speed of the improved algorithm model reaches 43 frames per second,the accuracy is 95.4%, the recall rate is 87.3%, and the mAP is 96.1%.Better results are obtained in the infrared UAV detection task.