In this paper we study the gain saturation induced mode-coupling control in solid state ring laser devices based on the stimulated Raman effect of the polar crystals in.order to realize solid state ring laser gyroscop...In this paper we study the gain saturation induced mode-coupling control in solid state ring laser devices based on the stimulated Raman effect of the polar crystals in.order to realize solid state ring laser gyroscopes. We theoretically investigate the mode coupling induced by gain saturation between clockwise （CW） and counterclockwise （CCW） propa- gating laser modes. Because the CW and CCW running waves are pumped with counter-propagating lasers respectively, the independent coexistence can be ensured.展开更多
This paper describes a novel approach for identifying the Z-axis drift of the ring laser gyroscope （RLG） based on ge-netic algorithm （GA） and support vector regression （SVR） in the single-axis rotation inertial ...This paper describes a novel approach for identifying the Z-axis drift of the ring laser gyroscope （RLG） based on ge-netic algorithm （GA） and support vector regression （SVR） in the single-axis rotation inertial navigation system （SRINS）. GA is used for selecting the optimal parameters of SVR. The latitude error and the temperature variation during the identification stage are adopted as inputs of GA-SVR. The navigation results show that the proposed GA-SVR model can reach an identification accuracy of 0.000 2 （？）/h for the Z-axis drift of RLG. Compared with the ra-dial basis function-neural network （RBF-NN） model, the GA-SVR model is more effective in identification of the Z-axis drift of RLG.展开更多
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 ...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.展开更多
文摘In this paper we study the gain saturation induced mode-coupling control in solid state ring laser devices based on the stimulated Raman effect of the polar crystals in.order to realize solid state ring laser gyroscopes. We theoretically investigate the mode coupling induced by gain saturation between clockwise （CW） and counterclockwise （CCW） propa- gating laser modes. Because the CW and CCW running waves are pumped with counter-propagating lasers respectively, the independent coexistence can be ensured.
文摘This paper describes a novel approach for identifying the Z-axis drift of the ring laser gyroscope （RLG） based on ge-netic algorithm （GA） and support vector regression （SVR） in the single-axis rotation inertial navigation system （SRINS）. GA is used for selecting the optimal parameters of SVR. The latitude error and the temperature variation during the identification stage are adopted as inputs of GA-SVR. The navigation results show that the proposed GA-SVR model can reach an identification accuracy of 0.000 2 （？）/h for the Z-axis drift of RLG. Compared with the ra-dial basis function-neural network （RBF-NN） model, the GA-SVR model is more effective in identification of the Z-axis drift of RLG.
文摘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.
