Abstract: In order to restore motion degradation blur of the strap-down guidance infrared seeker, a non-local sparse prior constraint modeling method for infrared images was proposed. By analyzing the infrared motion blur imaging features of the strap-down platform, a non-local sparse prior constraint modeling method based on motion information was proposed in the blind deconvolution framework, which can estimate the motion blur kernel of the image and restore the infrared motion blur image. The result shows that the non-local sparse prior constraint method based on motion information proposed in this paper is highly targeted and can effectively restore infrared motion blurred images with large motion amplitudes. Cumulative probability of blur detection, structural similarity, peak signal-to-noise ratio all show varying degrees of improvement, especially peak signal-to-noise ratio increases by nearly 8%, and the larger the motion amplitude, the more obvious the restoration results. This study lays the foundation for the application of the strap-down guidance infrared imaging system.