Novel approach for identifying Z-axis drift of RLG based on GA-SVR model

This paper describes a novel approach for identifying the Z-axis drift of the ring laser gyroscope (RLG) based on genetic 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 (degrees)/h for the Z-axis drift of RLG. Compared with the radial basis function-neural network (RBF-NN) model, the GA-SVR model is more effective in identification of the Z-axis drift of RLG.