For the questions of low utilization and precision in SAR image target recognition and classification ,the complicated operations and poor effect in the image feature extraction ,using the characteristics of the direction of sensitivity and the translation invariance of NSST for extracting the spectral texture features of SAR target image, proposing the method of target image recognition and classification based on the Multitask learning and Faster R-CNN. Building a network model of the multitask learning based on Faster R-CNN ,which can complete the recognition, identification and classification of SAR images at the same time .The results of the experiment show that this method still has a better recognition rate in the limited SAR images .And the algorithm is better than the traditional algorithm such as the NN ,SVM and Sc-SPM classification method. The average recognition rate can reach 98.13% in the publicly database of the MSTAR.