| With the continuously development of inertial devices,strapdown navigation inertial system(SINS)has been widely used in the key equipment field.Initial alignment plays a crucial role in navigational accuracy of SINS which depends on dead-reckoning algorithm.In order to improve the accuracy and stability of initial alignment,the coarse alignment methods of SINS are studied in this paper.The main research work of this paper is as follows:Firstly,the dual-vector attitude determination method is introduced and the analytical method based on vector averaging is proposed for the alignment process of the vehiclemounted SINS on the static base which effectively reduces influence of random noise from inertial sensors.Aiming at the alignment process of the swaying base,the inertial frame alignment method is studied,and the coarse alignment method on the swaying base with parameter identification is studied on the basis of the inertial frame alignment,improving the final alignment accuracy and convergence speed.Simulation results verify the correctness of the method.Secondly,for the alignment process of the vehicle-mounted SINS on the moving base,a coarse alignment method based on strict velocity integration is studied,and an attitude estimation method based on quaternion Kalman filter proposed.In view of the problem that the global positioning system(GPS)will produce outliers in some cases,the robust quaternion Kalman filter method is proposed based on the quaternion Kalman filter method and the magnitude-matching algorithm in Huber’s robust theory.The robust quaternion Kalman filter method can effectively reduce the influence of GPS outlier interference in the case of moving base alignment.In the case of GPS outliers,the convergence speed is accelerated compared with the traditional method,and the final alignment accuracy and stability are improved.The effectiveness of the method is verified by simulations and experiment results.Finally,aiming at the problem that the alignment result is easily affected by GPS outliers and the cumulative error of the gyro bias during the in-motion coarse alignment,the robust unscented Kalman filter initial alignment method is proposed which improves the convergence speed,accuracy and stability of the SINS moving base.The method estimates and removes the bias in the prediction equation,effectively reducing the influence of the gyro bias,and via magnitude-matching algorithm the hindrance of GPS outliers can be detected and eliminated.In order to improve the accuracy of the vector on the basis of reducing the influence of gyro bias,a robust coarse alignment method combining optimization and unscented quaternion Kalman filter is proposed,further enhancing the performance of the SINS moving base.Simulations and experiment results verify the effectiveness of the method. |
