Traditional submillimeter-wave imaging algorithms can image the target to be detected.However, due to the low-pass characteristics of the imaging system, high-frequency components in the signal are lost, resulting in the loss of details in the picture.On the other hand, the lobes are broadened in the course of signal processing, which may lead to aliasing of image points.Aiming at the shortcomings of the traditional algorithm in terms of poor imaging clarity and low resolution, this paper proposes a submillimeter-wave imaging super-resolution algorithm based on improved Projections Onto Convex Sets (POCS).This algorithm uses bilinear interpolation to obtain a high-resolution initial image.The initial image is subjected to iterative correction of convex set projection.Then, the adaptive correction threshold is introduced, and the correction threshold is dynamically adjusted by using the magnitude of the edge intensity, so as to achieve the purpose of accurate high-resolution restoration.Simulation results show that the algorithm can more accurately correct the pixels of the image, and improve the image resolution and imaging quality.