ISR-CDKF在SINS大方位失准角初始对准中的应用

针对捷联惯导系统（SINS: Strapdown InertialNavigation System）误差模型在大方位失准角条件下非线性的特点, 对非线性滤波算法的研究具有十分重要的意义。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。为克服以上不足,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 Difference Kalman Filter)算法, 并应用于SINS大方位初始对准中。通过滤波仿真, 进一步表明了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。

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

In case of that the error model of the strapdown inertial navigation system is nonlinear with large azimuth misalignment, it is very significant to study the nonlinear filter algorithm. 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 utilizedin initial alignment. The results of simulation show that the ISR-CDKF has higher precision and convergence, and has stronger numerical stability.