The Research of High Performance Fiber Optic Gyroscope SINS/GPS Integrated Navigation System for Vehicle

摘要

The FOG SINS/GPS integrated navigation system has the advantage of inertial navigation and satellitic navigation synchronously, so it can be applied widely to the military and civilian domain. Nowadays, large numbers of people pay more attention to its application in vehicle condition. The Kalman filter is a method to dispose integrated navigation information, by making full use of the observations to estimate the state variables. But the noise parameters of the filter are only from classical statistics. With the extension of applications of vehicle FOG SINS/GPS integrated navigation system, the noise disturbers change fluently at the same time. Both the system noise of inertial instruments and the observation noise of GPS alter stochastically along with the environment's diversification. In this situation, the filter parameters do not conform to the facts. They influence the convergent rate of the system, as well as lead the radiation of the system. Based on the fuzzy logical theory, and in allusion to the noise about the vehicle FOG SINS/GPS integrated navigation system, the paper analyzes the character of noise transformation in different conditions, such as the general environment and the dynamic dicky environment. According to the connection between the inputs and outputs of fuzzy logical theory, the fuzzy deducible algorithm is given. It is a kind of on-line adaptive kalman filter. In this way, further research on the information fusion of FOG SINS/GPS integrated navigation system is performed. The statistical models of the noise arising from the general environment and dynamic dicky environment are presented, their relation is given as well. Through the simulation and experimentation, the dependence of the newest information on the noise model is investigated. The paper designs a series of factors. They are the range ground on the fuzzy logical input-output, subject functions and rational scheme. This algorithm makes the mean of the filter innovation, ratio between the real covariance and the academic covariance of the filter innovation as the inputs of the fuzzy illation system. In order to make the fuzzy gather change into the accurate outputs which can be identified by integrated navigation system, the barycenter algorithm is adopted at the same time. The weights of covariance about the observation noise and the system noise are modified on line so as to approach the real value quickly. This algorithm can realize the best estimate of information fusion to improve the reliability and precision of integrated navigation system. The static experiment indicates that the method shortens the convergent time of static integrated navigation, while the dynamic experiment indicates that the method improves the system precision by about 20%. It is a realizable method, of which computation does not increase remarkably.