Chinese Optics Letters, 2011, 9 (5): 051201, Published Online: Apr. 22, 2011
Novel temperature modeling and compensation method for bias of ring laser gyroscope based on least-squares support vector machine Download: 733次
激光陀螺 最小二乘支持向量机 最小二乘估计 逐步回归分析 120.0120 Instrumentation, measurement, and metrology 120.5790 Sagnac effect 140.3370 Laser gyroscopes 280.4788 Optical sensing and sensors
Abstract
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. The results show the maximum error of RLG bias drops by almost two orders of magnitude after static temperature compensation, while bias stability of RLG improves by one order of magnitude after dynamic temperature compensation. Thus, the proposed method reduces the influence of temperature variation on the bias of the RLG effectively and improves the accuracy of the gyro scope considerably.
Xudong Yu, Yu Wang, Guo Wei, Pengfei Zhang, Xingwu Long. Novel temperature modeling and compensation method for bias of ring laser gyroscope based on least-squares support vector machine[J]. Chinese Optics Letters, 2011, 9(5): 051201.