Altitude information fusion method and experiment for UAV

Altitude regulation is a fundamental problem in UAV ( unmanned aerial vehicles) control to en-sure hovering and autonomous navigation performance.However, data from altitude sensors may be unstable by interference.A digital-filter-based improved adaptive Kalman method is proposed to im-prove accuracy and reliability of the altitude measurement information.A unique sensor data fusion structure is designed to make different sensors switch automatically in different environment.Simula-tion and experimental results show that an improved Sage-Husa adaptive extended Kalman filter ( SHAEKF) is adopted in altitude data fusion which means that altitude error is limited to 1.5m in high altitude and 1.2m near the ground.This method is proved feasible and effective through hove-ring flight test and three-dimensional track flight experiment.