Infrared image simulation plays an important role in the design and training of infrared seeker.Aiming at how to simulate infrared images with high resolution and controllable visual features,a method of infrared image simulation based on progressive generative adversarial network is proposed.In this paper,the infrared images dataset of warship model is used to train the image synthesis network,only random feature vector is necessary for the generation of high resolution infrared simulated image.An image encoder network is designed to convert infrared images to feature vectors.By the logistic regression method,the direction vector which controls the angle feature of infrared images is found in the feature vector domain,and simulated images of warship model from different angles are generated accordingly.AHash algorithm and MSSIM algorithm are used to quantitatively evaluate the difference between simulated and real images.The experimental results show that the similarity between the simulated infrared images and the real ones is very high,and it can be used as a reference for the controllable simulation of real warship infrared images.