一种GPS辅助的低精度捷联惯导动态对准方法

Low accuracy SINS dynamic alignment method based on CKF aided by GPS location information

针对低精度SINS的陀螺不能辨识地球自转角速度,难以完成自对准的问题,该文引入GPS的位置观测信息利用5级-CKF简化算法辅助低精度SINS完成初始对准;因为低精度SINS粗对准给出的初始姿态质量很差,不满足小失准角的条件,所以必须采用大失准角非线性误差模型和非线性滤波方法。该文提出5级-CKF算法,并在系统模型噪声和量测噪声均为加性噪声且量测方程为线性方程时,对5级-CKF算法进行简化,其需要在kalman滤波的基础上利用5级容积采样点对非线性状态方程的状态及其方差进行预测。设计仿真实验验证了该方法的有效性,并分析了大失准角情况下载体运动状态对航向角估计的影响。

Against tlhe low accuracy SINS that with too low accuracy Gyro to measure the Earth＇s ro- tation angular velocity tlhat cannot complete self-alignment, the coordinate information of GPS was intro- duced and a simplified 5th-CKF was used to assist the SINS to complete alignment in this paper. Due to the attitude given by low accuracy SINS＇s coarse alignment cannot meet the conditions of small misalign- ment angle, a simplified 5th-CKF was deduced under the situation that both process noise and measure- ment noise were additiw.~ noise with liner measurement equation. The simplified 5th-CKF was identical to that of classical Kalman filter except for the predicting of states and their covariance matrix by spherical-radial cubature rule. Simulation results showed that the simplified 5th-CKF was useful under large misalignment angle, and the estimated impact on heading angle of the moving states of the body was analyzed.