Research On Noise Control Technology In Fiber Optic Gyroscope Based On Variable Order Least Mean Square Algorithm

The inertial navigation system requires the fiber optic gyroscope(FOG)to have a good suppression effect on the system output random noise.The suppression level of the fiber optic gyroscope is one of the important factors affecting the accuracy of the navigation system.The Sagnac phase shift detected by the system is a small amount of information relative to each noise term,and is often submerged in the system optical path and circuit noise.Reducing the output noise of the system,extracting the useful signal quickly and easily,and improving the detection accuracy of the FOG play a vital role in further research of the fiber optic gyroscope.As a closed-loop all-digital high-precision system,the use of digital filtering to suppress noise is of great significance for improving the accuracy of FOG.This paper is devoted to solving the problem of how to effectively and quickly reduce the noise of the FOG output system,using the adaptive filtering algorithm to digitally filter the system output data.The fractional mean-order least mean square(FTLMS)algorithm and its improved algorithm are applied to suppress the noise effect in the output information of the FOG.This paper mainly contains three parts.The first part analyzes the basic principle of closed-loop FOG in detail,and deeply studies the causes of system output noise.In order to effectively suppress the noise level of FOG,the noise generation mechanism of the interferometric fiber optic gyroscope system is analyzed,and the statistical characteristics of each noise term are analyzed by Allan variance.A variable-order least mean square(LMS)algorithm is applied to design a noise suppression scheme for adaptive filters based on fractional-order least mean square(FTLMS)algorithm.The filter is effectively converged to the optimal order,and the weight of the filter is adaptively adjusted to more quickly and effectively suppress the noise level in the output information of the system.In the second part,the iterative parameters and error width of the variable order LMS algorithm are improved and optimized.The VP-FTLMS algorithm which changes the iterative parameters and the VW-FTLMS algorithm which changes the error width are developed,and its convergence performance and tracking performance are The simulations in low noise and high noise environments are carried out.The analysis results show that the improved algorithm improves the convergence fastness and dynamic tracking.The convergence performance and tracking performance of the FTLMS algorithm are improved,with faster order convergence speed,smaller steady-state oscillation and smaller additional mean square error,which well solves the order iteration in the variable order LMS algorithm.The contradiction between convergence speed and steady-state oscillation avoids the problem that the algorithm falls into the local optimal solution and cannot converge to the true optimal solution.In the third part,the actual noise reduction experiment of the adaptive filtering algorithm is carried out by using the actual data of the FOG to verify the effectiveness of the proposed algorithm and its improved algorithm.1)contrast experiments of different order filtering noise suppression effects based on FTLMS algorithm,using Allan variance method to verify the correctness of the best order convergence;2)comparison experiment of actual gyro noise reduction effects of several different algorithms(average filter,FTLMS,VP-FTLMS,VW-FTLMS).It is proved that the improved algorithm has better noise suppression effect than other algorithms,and has important engineering significance for improving the accuracy of FOG and the performance of inertial navigation system.