Abstract: Aiming at the airborne integrated navigation system, considering the air pressure altitude in different flight stages, an improved Sage-Husa adaptive filtering algorithm is proposed to improve the positioning accuracy of the integrated navigation system. This algorithm calculates and corrects the adjustment factor of filter anomaly determination in real time by introducing air pressure altitude to meet the filtering requirements of different flight stages of the aircraft. Through strap-down inertial navigation system (SINS), global navigation satellite system (GNSS) positioning error characteristics simulation, Kalman filter combination algorithm simulation, and improved Sage-Husa The adaptive filtering algorithm is simulated, and the relevant results are compared and verified. The simulation results show that improving the Sage-Husa adaptive filtering can improve the adaptiveness of the filtering, reduce the positioning error of the integrated navigation system, and achieve better results.