基于支持向量机的MEMS陀螺仪随机漂移补偿  

Random Drift Compensation of MEMS Gyroscope Based on Support Vector Machine

作　　者：李泽民[1] 段凤阳[1] 马佳智[1] 

机构地区：[1]空军航空大学航空控制工程系,长春130022

出　　处：《传感技术学报》2012年第8期1084-1087,共4页Chinese Journal of Sensors and Actuators

基　　金：武器装备重点预研项目(40405030403)

摘　　要：针对传统方法的不足,将支持向量机应用于MEMS陀螺仪随机漂移的补偿。建立了支持向量机预测模型,通过相空间重构技术,将标量的随机漂移时间序列嵌入到一个辅助的相空间中进行模型的训练和测试,并使用最优化算法得到了核函数和预测模型的各项参数。训练和预测结果均表明,该方法具有很好的预测效果,是一种有效的MEMS陀螺仪随机漂移补偿方法。Support vector machine has been applied to the compensation of MEMS gyroscope random drift to overcome the disadvantages of traditional methods.The support vector machine prediction model is established firstly in order to train and test the model,then embedding the scalar gyroscope random drift time series to an assistant phase space by the technology of phase construction.The best parameters of core function and prediction model are get by using the optimization algorithm.Both the train and test results show that this method can predict the gyroscope random drift well.It is an effective compensation method to MEMS gyroscope random drift.

关 键 词：MEMS陀螺仪 随机漂移 支持向量机 相空间重构 

分 类 号：V241.5[航空宇航科学与技术—飞行器设计]