Novel temperature modeling and compensation method for bias of ring laser gyroscope based on least-squares support vector machine

• 来源期刊: 中国光学快报（英文版）
• 年，卷（期）: 2011,（5）
• 页码范围: 37-40
• 页数: 4页
• 语种: 英文
• DOI: 10.3788/COL201109.051201.

摘要

Bias of ring-laser-gyroscope (RLG) changes with temperature in a nonlinear way.This is an important restraining factor for improving the accuracy of RLG.Considering the limitations of least-squares regression and neural network, we propose a new method of temperature compensation of RLG bias-building function regression model using least-squares support vector machine (LS-SVM).Static and dynamic temperature experiments of RLG bias are carried out to validate the effectiveness of the proposed method.Moreover,the traditional least-squares regression method is compared with the LS-SVM-based method.