Abstract: This article studied the movement state estimation based on the vision image process for unmanned helicopter (UH) landing. The vision-based landing principle and scheme is introduced, and the relationship between movement state estimation, feature image process and landing control is analyzed. The movement state estimation algorithms are deduced and modeled, which include a relative position to the landing pad and attitude estimation algorithm, and a velocity and angular rate estimation algorithm. The pixel positions of the corresponding feature points from two sequent image frames are provided for the relative position and attitude estimation algorithm. The pixel positions and pixel translation velocities of the corresponding feature points from one image frame are provided for velocity and angular rate estimation. Simulated imaging data from UH landing control simulation imitated the feature pixel positions and their corresponding pixel translation velocities. Simulation and verification for the movement state estimation is conducted. Simulation results indicate that the proposed movement state estimation algorithm can estimate effectively the position, attitude, velocity and angular rate with the vision image process data.

Key words: unmanned helicopter landing, computer vision model, motion estimation, vision algorithm simulation, flight imaging data simulation