基于大方位失准角条件下捷联惯导系统误差模型的非线性特点,采用非线性滤波方法进行初始对准.扩展卡尔曼滤波存在精度低,且需要计算雅可比矩阵等不足,而中心差分卡尔曼滤波在递推过程中具有计算量大,数值不稳定等缺点.针对上述问题采用了一种改进的中心差分滤波算法一一平方根中心差分卡尔曼滤波.仿真结果表明,与扩展卡尔曼滤波相比,平方根中心差分卡尔曼滤波对方位失准角的对准精度由24.5′提高到5.83′,并且避免了计算雅可比矩阵带来的不便;与中心差分滤波相比,平方根中心差分卡尔曼滤波在保证滤波精度的同时,降低了滤波的计算量,提高了滤波的数值稳定性.%Based on the characteristics that the error model of the strapdown inertial navigation system is nonlinear when with large azimuth misalignment, the nonlinear filtering methods are utilized in initial alignment. The extended Kalman filter has low precision and requires the computation of Jacobian matrix,and the central difference Kalman filter has the problem of numerical instability and large amount of computation in recursive processes. In view of the above problems, the modified square root central difference Kalman filter is applied to the system. Simulation results show that, compared with the extended kalman filter, the azimuth alignment accuracy can be improved form 24.5′ to 5.83′, and the square root central difference Kalman filter does not need calculate the Jacobian matrix. And compared with the central difference Kalman filter, the square root central difference Kalman filter can significantly reduce the amount of calculation and improve the numerical stability with accurate alignment.
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