A Segmented AEKF Method for Trajectory Estimation of Dual-spin Flight Vehicles

A segmented adaptive extended Kalman filter (AEKF) method for trajectory estimation was proposed to solve the problem of degraded navigation accuracy in navigation systems due to significant errors in satellite information, caused by dynamic characteristics of dual-spin flight vehicles such as high overload, high speed and high spin. According to the dynamic characteristics of dual-spin flight vehicles, a flight phase division method was proposed, and specific flight phases were associated with the noise estimator parameters of AEKF algorithm, so that the measurement noise covariance matrix could be adjusted adaptively during the flight, to estimate the trajectory and improve the positioning accuracy of the vehicle. Flight tests showed that this method can effectively reduce the positioning error and enhance the adaptability of the navigation system.