摘要
Euler angle error model, rotation vector error model （RVE） and quaternion error model （QE） were qualitatively and quantitatively compared and an in-flight alignment filter algorithm was designed. This algorithm used extended Kalman filter （EKF） based on RVE and QE separately avoi- ding the accuracy problem of the Euler angle model and used Rauch-Tung-Striebel（RTS） smoothing method to refine the accuracy recuperating the coning error for simplified RVE. Simulation results show that RVE and QE are more adapt for nonlinear filter estimation than the Euler angle model. The filter algorithm designed has more advantages in convergence speed, accuracy and stability comparing with the algorithm based on the three models separately.
Euler angle error model, rotation vector error model （RVE） and quaternion error model （QE） were qualitatively and quantitatively compared and an in-flight alignment filter algorithm was designed. This algorithm used extended Kalman filter （EKF） based on RVE and QE separately avoi- ding the accuracy problem of the Euler angle model and used Rauch-Tung-Striebel（RTS） smoothing method to refine the accuracy recuperating the coning error for simplified RVE. Simulation results show that RVE and QE are more adapt for nonlinear filter estimation than the Euler angle model. The filter algorithm designed has more advantages in convergence speed, accuracy and stability comparing with the algorithm based on the three models separately.
