基于惯性系采用Kalman滤波的车载SINS行进间对准方法

摘要

An alignment method with inertial frame based on gravity information was described. On this basis, the strap-down inertial navigation system (SINS) error equations which use the geocentric inertial frame as the navigation reference frame were deduced. A state model which matches the inertial frame a-lignment algorithm was established, and a novel SINS alignment algorithm based on inertial frame filtering for marching vehicles was proposed. Computer simulation results demonstrate that the initial alignment algorithm based on inertial frame filtering for marching vehicles can solve the problem of large interference angular velocity. Real-time filter scheme can further reduce the effect of the noise and improve the accuracy of initial alignment. Besides, compared with the alignment algorithm based on geographic frame filtering, it simplifies the model and reduces the computational complexity.%介绍了惯性系中基于重力加速度信息进行粗对准的实现方法.在此基础上通过推导以地心惯性坐标系为导航系的捷联惯性导航系统(SINS)误差方程,建立了与惯性系对准算法相匹配的状态模型,提出了一种采用Kalman滤波实现基于惯性系的SINS行进间精对准方法.计算机仿真实验结果表明,文中所提出的基于惯性系的采用Kalman滤波的车辆行进间精对准方法,可有效地降低干扰噪声的影响,提高初始对准的精度.此外,该方法相对于基于地理坐标系进行滤波的方法,简化了滤波模型,较大的降低了计算量.