The real-time performance and accuracy of the algorithm for UAV ranging are always the focus of research.As for the real-time performance of the algorithm, a bidirectional search strategy and three data streams are proposed to accelerate the GPU, and a butterfly sorting algorithm is introduced to improve the computing efficiency.As for the accuracy of the algorithm, the improved Absolute Difference (AD) algorithm is combined with the improved Census algorithm, which effectively solves the problem that the algorithm relies too much on the center pixel.In order to reduce the complexity of the algorithm, the moving average algorithm is introduced into target detection based on the background subtraction method.As for the limited storage space of UAV platform, an optimization scheme of data storage is proposed to reduce the space occupied by data.A comparison with Boyer-Moore (BM) algorithm and Semi-Global Block Matching (SGBM) algorithm is conducted on Middlebury data set, and then the outdoor scenes are collected for the comparison with BM algorithm on ranging performance.Finally, the UAV ranging is implemented outdoors.A large number of experimental data has verified that the algorithm meets the high precision requirements of UAV real-time ranging.