Aming at the difficulty of image matching caused by different imaging modes,time phases and resolutions of heterogeneous remote sensing images,a remote sensing image matching algorithm based on cycle generative adversarial strategy is proposed.A cross-data domain image feature migration cycle generative adversarial network (GAN) was constructed,a SmoothL1 loss function was designed to optimize the network,the accuracy of remote sensing image feature extraction was improved,and based on the result of image feature migration,triple margin ranking loss function (TMRL) was established to reduce remote sensing image mismatched points,to achieve accurate matching of heterogeneous remote sensing images.The test results show that the method in this paper improves the average accuracy of heterogeneous remote sensing image matching by 33.51%,and has a better remote sensing image matching effect than the cross modality matching net (CMM-Net) method.In addition,this method not require the annotation information of the target domain image,and the matching time is shortened by 0.073 s,which can quickly and accurately achieve heterogeneous remote image matching.