Research on stochastic error suppression method of FOG based on quasi-proportional information

Abstract

Abstract In order to improve the precision of fiber optic gyro (FOG), it is necessary to suppress the stochastic error effectively. Therefore, the stochastic error suppression of FOG is studied. Firstly, the data of FOG at room temperature and variable temperature are analyzed. Then, a general form of FOG random error model is derived, and an adaptive filtering method based on quasi-proportional information is proposed to estimate the process noise covariance effectively. At last, the room temperature experiment, the variable temperature experiment and the dynamic experiment are carried out. Compared with the recently proposed adaptive filter algorithm, the variance reduction of the proposed algorithm at the average time of 33 s, 54 s and 55 s is more than 70%, and the suppression effect of the algorithm on the random walk coefficient is improved by more than 2%, showing strong robustness.