Aiming at the sensor fault problem of Unmanned Aerial Vehicle (UAV) during multi-sensor fusion navigation,a method for diagnosing GPS sensor faults using inertial navigation sensors is proposed to achieve mutual fault diagnosis between sensors.When performing pose calculation on sensor data during UAV navigation,considering the status residual information generated by Extended Kalman Filter (EKF) in the prediction and update process of sensor data in navigation,namely the position information calculated by both inertial navigation and GPS,a sensor fault diagnosis method based on improved Sequential Probability Ratio Test (SPRT) is designed.It improves the sensitivity of the SPRT algorithm to abrupt changes in residual information and the diagnostic sustainability in multiple fault situations.Data simulation experiments show that,compared with traditional methods and other improved algorithms,this method can detect the time when faults occur and disappear quickly and accurately,and continuously diagnose faults,which improves the flight safety of UAVs greatly.