A New Open-Loop Fiber Optic Gyro Error Compensation Method Based on Angular Velocity Error Modeling

With the open-loop fiber optic gyro (OFOG) model, output voltage and angular velocity can effectively compensate OFOG errors. However, the model cannot reflect the characteristics of OFOG errors well when it comes to pretty large dynamic angular velocities. This paper puts forward a modeling scheme with OFOG output voltage [Formula: see text] and temperature [Formula: see text] as the input variables and angular velocity error [Formula: see text] as the output variable. Firstly, the angular velocity error [Formula: see text] is extracted from OFOG output signals, and then the output voltage [Formula: see text] , temperature [Formula: see text] and angular velocity error [Formula: see text] are used as the learning samples to train a Radial-Basis-Function (RBF) neural network model. Then the nonlinear mapping model over T, [Formula: see text] and [Formula: see text] is established and thus [Formula: see text] can be calculated automatically to compensate OFOG errors according to [Formula: see text] and [Formula: see text]. The results of the experiments show that the established model can be used to compensate the nonlinear OFOG errors. The maximum, the minimum and the mean square error of OFOG angular velocity are decreased by [Formula: see text] , [Formula: see text] and [Formula: see text] relative to their initial values, respectively. Compared with the direct modeling of gyro angular velocity, which we researched before, the experimental results of the compensating method proposed in this paper are further reduced by [Formula: see text] , [Formula: see text] and [Formula: see text] , respectively, so the performance of this method is better than that of the direct modeling for gyro angular velocity.