晃动基座下激光陀螺捷联导航系统初始对准预滤波新方法

激光陀螺捷联惯性导航系统在晃动基座下进行初始对准，外界的干扰会令激光陀螺和加速度计的噪声增大，从而使初始对准的时间延长，甚至不能完成对准。对激光陀螺和加速度计输出简单的采用低通滤波的方法，并不能有效的抑制传感器噪声。采用小波方法，虽然能够抑制噪声的影响，但是由于小波的高计算复杂度和块处理结构，很难在线实现。针对这个问题，本文提出一种新的预滤波方法，将传感器输出通过低通滤波之后再通过一个基于隐式马尔可夫模型的稳态卡尔曼滤波，这样就能有效的降低基座晃动带来的噪声，同时不降低对准的精度。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，能够很好的辅助激光陀螺捷联导航系统在晃动基座下完成精对准。

Prefiltering for initial alignment of ring laser gyroscope SINS on rocking base

When the initial alignment of ring laser gyroscope SINS is performed on a rocking base, the noise of ring laser gyroscopes and accelerometers will increase. Then, it will need more time to accomplish the initial alignment. Sometimes, the large noise will make the alignment fail. Only with a lowpass filter, the output of sensors will still suffer from large noise. Wavelet can suppress the noise brought by the dither motion of base. However, it has a high computational complexity and block-processing structure, which makes it hard to be implemented online. To solve this problem, a new prefilter method is proposed in this paper. After the output of sensors is filtered by the lowpass filter, a steady-state Kalman filter which uses a hidden Markov model will be used to filter it. Then, the large sensor noise brought by the dither motion of base can be lowed down to a very low level. Experiment results show that this prefilter method can work efficiently with a low computational complexity and help SINS accomplish the initial alignment on a rocking base.