In SAR image target detection based on deep learning,in order to reduce the interference of noise and other characteristics in SAR images on feature learning and improve the interactivity of identifying and locating tasks in detection methods,a joint task detection method is adopted.The method makes use of the joint task network,so that the identification and location tasks share features as much as possible while retaining their own particularities,thus improving the supervision ability of the two types of tasks on feature learning.In addition,the method also uses the joint task learning method,and considers the reliability of identifying and locating tasks in the selection of anchor frame and the calculation of loss function,thus improving the training effect.The experimental results on public dataset prove the effectiveness of the method.