ISR-CDKF在SINS大方位失准角初始对准中的应用

Application of ISR-CDKF in Initial Alignment of Large Azimuth Misalignment in the SINS

扩展卡尔曼滤波(EKF:Extended Kalman Filter)精度低,而且需要计算复杂的雅可比(Jacobian)矩阵;而中心差分卡尔曼滤波(CDKF:Central Difference Kalman Filter)虽然精度稍高,但计算量大,且算法不稳定。为此,提出了迭代测量更新的平方根中心差分卡尔曼滤波(ISR-CDKF:Iterative Square Root Central DifferenceKalman Filter)算法,并应用于SINS大方位初始对准中。通过滤波仿真表明,ISR-CDKF算法不仅具有更高的精度和收敛性,同时具有较强的数值稳定性。

The precision of EKF （Extended Kalman Filter） is low, which needs to calculate the complex Jacobian matrices. Although the theoretical precision of CDKF （Central Difference Kalman Filter） is a little higher, the amount of calculation is large and the algorithm is unstable. To overcome the above shortcomings, the ISR-CDKF （Iterative Square Root Central Difference Kalman Filter） is proposed, and is utilized in initial alignment. The results of simulation show that the ISR-CDKF has higher precision and convergence, and has stronger numerical stability.