针对激光陀螺捷联惯性导航系统在晃动基座下进行初始对准时激光陀螺和加速度计噪声过大，而采用低通滤波或小波方法不能有效实时地实现噪声抑制的问题，提出一种采用IIR低通滤波器和基于隐式马尔可夫模型的稳态卡尔曼滤波相结合的新的预滤波方法。首先，将传感器输出通过低通滤波，然后，再通过一个基于隐式马尔可夫模型的稳态卡尔曼滤波，从而有效地降低基座晃动带来的噪声，而不降低对准精度。实验结果表明，本文提出的预滤波方法计算复杂度低，滤波效果明显，在发动机开动的情况下，可以把导航系统激光陀螺的噪声标准差由300°/h降至1°/h，加速度计的噪声标准差由11 mg降至40 μg。结果表明，提出的预滤波器能够很好地辅助激光陀螺捷联导航系统在晃动基座下完成精对准。

As the laser gyroscopes and accelerometers in a ring laser gyroscope Strapdown Inertial Navigation System(SINS) generate high noises by the dither motion of a base and a low pass fitering and a wavelet method can not suppress the noises in real time effectively,this paper presents a prefiltering method combining a low pass filtering and a Kalman filtering based on a hidden Markov model.Firstly, the output of a sensor is filtered by the lowpass filter,then it is filtered by the steady-state Kalman filter based on the hidden Markov model.By this way, the large sensor noise brought by the dither motion of the base can be lowed down to a very low level. Experiment results show that this prefiltering method can work efficiently with a low computational complexity. When the vehicle engine is on, the standard variances of the ring laser gyroscope and accelerometer are suppressed from 300°/h to 1°/h and from 11 mg to 40 μg, respectively. It is concluded that the proposed prefiltering can help SINS accomplish the initial alignment on a rocking base.