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Temperature compensation for mechanically dithered RLG bias based on K-means Clustering

机译:基于K-Means聚类的机械抖动RLG偏置温度补偿

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The temperature characteristic of mechanically dithered ring laser gyroscope (RLG) has been studied, based on temperature experiment. Using the method of clustering, analyzed the output of the temperature sensor. Finally, the segmented data was compensated, and the result was compared with that of full temperature data compensation. The results show that: the model of full temperature data compensation method is incomplete. There is still much room for improvement. In this paper, the segmented data compensation model by using clustering analysis method can compensate the gyro bias, improve the gyro accuracy.
机译:基于温度实验,研究了机械抖动环激光陀螺仪(RLG)的温度特性。使用聚类方法,分析了温度传感器的输出。最后,补偿了分段数据,并将结果与​​全温数据补偿进行了比较。结果表明:全温数据补偿方法模型不完整。还有很多改进空间。在本文中,通过使用聚类分析方法进行分段数据补偿模型可以补偿陀螺偏压,提高陀螺准确性。

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