In order to solve the problem of realization of UAV autonomous navigation in the environment of weak GPS signal or rejection, an optical flow/inertial integrated navigation method suitable for complex texture environment is proposed. Through the improved lucas and kanade (LK) optical flow method based on low-texture scenes, the image optical flow information is calculated, the inertial navigation system information is used to assist the optical flow navigation system, and the characteristic point speed information of the optical flow navigation system is also used to assist the inertial navigation system for navigation solution, use Kalman filter to fuse optical flow/inertial navigation information to obtain speed and position estimation information, and verify it through simulation experiments. Simulation results show that this method can accurately estimate speed and position information in scenes with rich textures and poor textures. The proposed navigation algorithm meets the real-time and accuracy requirements of autonomous navigation.