Research On Compensating Functional Error Of INS/GNSS Integrated Navigation

INS/GNSS integrated navigation is more available continuous,and reliable than INS or GNSS.However,if the signal of GNSS is interrupted,the accuracy of INS/GNSS integrated navigation system will be degraded rapidly as the accuracy of the system is strongly depended on GNSS observations.This thesis focuses on the system accuracy during absence of the GNSS observations.The following studies are carried out to improve the positioning accuracy of the integrated system:1.The algorithm of strapdown inertial measurement unit(IMU)is introduced.The rotation matrix of different coordinate system and equivalent rotation vector is discussed.A test of IMU is implemented.The test shows that INS accuracy cannot be remained as the system error accumulate along with time.The error formulation is derived and the implementation of loosely coupled and tightly coupled are given.3.The error analysis of 3DM-GX5-25 is presented with Allan Variance.The analysis indicates that angle random walk and bias is main noise in 3DM-GX5-25.4.The correlation time of the first Gauss-Markov model is estimated by autocorrelation function.A static test is presented with 14 hours data of STIM300.The results indicate that the autocorrelation function could not proper estimate the noise parameter of the sensors.The data indicate that the gyroscope measurements of STIM300 are low correlated that the correlation time cannot be accurate estimated by autocorrelation function.This thesis use ARMA model to model the bias of IMU.The static analysis indicate that the bias can be effectively modeled by ARMA instead of first Gauss-Markov model.5.In this thesis,the functional error of dynamic model is predicted by time series analysis method.The mathematical expression of the function is presented.The predicated functional model can compensate the system bias while GNSS signal is blocked.A field test is carried out to verify the proposed algorithm.The result indicate that the predicted functional error can suppress the divergence of the error of the integrated navigation system to some extent.