Optimization Method Research Of SINS Transfer Alignment Based On Observability Analysis

Transfer alignment is a commonly fast and efficient way of initial alignment by far,which has the short time and high alignment accuracy.But due to the ability of the filter estimates the misalignment angle between the master and slave inertial navigation system is affected by the system states' observability in the process of alignment,it leads to the transfer alignment accuracy dose not meet the ideal requirements in some objective conditions.Based on the observability analysis of the system states,the optimization method to improve the transfer alignment accuracy of strapdown inertial navigation system is stuied deeply in this paper.First of all,the basic theory used in the transfer alignment of strapdown inertial navigation system is given,it mainly includes: the definition of the coordinate which are commonly used in transfer alignment;real-time updating algorithm of attitude matrix;the transfer alignment filtering model of two common matching algorithms;the discrete kalman filter basic recursive equation used in the transfer alignment.Secondly,the methods for analyzing observability and observation degree are studied.And several common methods used in the past are given,including the directed graph method,the ???????? observation degree method,the error covariance eigenvalue method and the observability matrix eigenvalue method.By summarizing their features,their limitations and application range are obtained.After the basic principle and specific implementation process of singular value decomposition method for determining the system state observation degree are discussed,and the correctness of singular value decomposition method in analyzing the system state observation degree in transfer alignment is verified effectivly under the specific background.Next,according to the motor characteristics of the ship during the alignment process at sea,and on the basis of the establishment of transfer alignment speed matching and velocity plus attitude matching filtering model,the system state observation degree of the two matching methods under different motor ways are discussed by using singular value decomposition method,and the filter estimation effect under different motor ways are also discussed.The inner relationship between the alignment result and the observability of system state is verified effectivly by the simulation analysis.And then combined with the actual situation of the system state observability,the best matching algorithm in the condition of specific motor which has good alignment effect is given.The simulation and experiment results show that the speed matching transfer alignment method should be choosed under static or low power motor condition,and when the ship is swing,the velocity plus attitude matching algorithm should be choosed.Finally,the optimization methods to improve the precision of transfer alignment are studied deeply.In the case of knowing the observability,dimension reduction filter design method is given,and the full and reduction dimension filter model of transfer alignment is analyzed by the simulations,the rationality of the reduced-order filter design are validated effectivly by the simulation results.Then,the kalman filter optimization method based on the group of state is given,the conventional kalman filtering gain is attenuation according to the observation degree,aiming at solving the problem of low precision of transfer alignment filter estimation due to the poor observability.It can improve the adaptability of transfer alignment filtering algorithm in different environments.The simulation experiment results show that the optimization method can effectively improve the accuracy of transfer alignment,and it also can reduce the alignment time drastically.