针对非线性误差模型的状态估计精度差、收敛时间长、计算量大等缺点,描述了一种基于双模型切换的二次传递对准方法.该方法采用了常用的基于欧拉角的线性误差模型和基于四元数的非线性误差模型.在第一次对准中采用非线性模型与扩展卡尔曼滤波,待子惯导姿态失准角收敛到较小角度后进行模型与滤波切换;在第二次对准中采用线性模型与常规卡尔曼滤波来完成传递对准,从而获取更高的对准精度.通过仿真与跑车试验,证明了该方法能够满足系统的快速性与精确性要求,具有一定的实用性.

In view of the problems that the state estimation of nonlinear error model has the shortcomings of long convergence time,low estimation accuracy,and large calculation cost,a twice rapid transfer alignment algorithm based on dual-model switching is presented.The commonly-used linear error model based on Euler angles and nonlinear error model based on quaternion were utilized. In the first phase,the nonlinear error model and extended Kalman filter were used.Then,when the attitude misalignment angle converges to a certain degree,the linear error model based on Euler angles and the conventional Kalman filter were adopted in the second alignment to get higher accuracy.The simulation and vehicle test results demonstrate that this method is feasible and can meet the requirements to accuracy and rapidity.