采用马尔可夫链的光纤陀螺温度建模与补偿

FOG temperature model-building and compensation based on Markov Chain

由于光纤陀螺各组件对温度敏感,因此温度成为影响光纤陀螺精度的重要原因之一。为了消除温度效应并提高陀螺精度,通常采用对光纤陀螺进行温度建模的方法对其输出进行补偿。在对随机过程中的马尔可夫过程进行深入研究的基础上,推导出了单入单出系统的一阶受控马尔可夫链与差分方程的关系,并以此为依据建立了光纤陀螺温度模型,利用时齐转移概率对模型进行辨识,最后利用蒙特卡罗方法进行补偿后的结果仿真。通过对比补偿前后的输出可以看出,使用该方法建立的模型具有较好的预测效果,具有一定的应用前景,对光纤陀螺温度补偿工程化实现有一定的意义。

Temperature is one of the most important reasons that affect the FOG accuracy since the FOG components are sensitive to temperature. In order to eliminate temperature effect and improve precision, temperature modeling method is generally adopt. Based on the studying of the Markov process of stochastic process, we deduced the relationship between the first controlled Markov Chain and the difference equation in SISO system, and based on this, we established FOG temperature model. We utilized time homogeneous transition probability to identify the model and used Monte Carlo method to simulate the compensated output of FOG Compared with the uncompensated output, we can see that the model based on the first controlled Markov Chain has good prediction effect and application prospect, and has significance to the engineering realization of FOG temperature compensation.