Research On Improving Accuracy Of SINS/GNSS Integrated Navigation System Under Abnormal Measurement Signals

The SINS/GNSS integrated navigation system combines Strapdown Inertial Navigation System(SINS)and Global Navigation Satellite System(GNSS).It corrects SINS errors and helps SINS to complete navigation tasks by providing the velocity and position of the GNSS.Especially,since BeiDou Navigation Satellite System network has been completed,it is an important direction to relay on GNSS to achieve high-precision navigation for integrated navigation system.However,the power of satellite signals reaching the ground is very weak,and the road conditions are complicated.Satellite signals are easily be affected by the interference such as multipath and occlusion.As a result,the velocity and position measurement information provided by the GNSS is abnormal.The navigation precision of integrated navigation system will face great challenges.Therefore,the research on SINS/GNSS integrated navigation system technology under abnormal measurement is an effective way to improve the navigation performance.It is also important for the engineering application of propulsion SINS/GNSS integrated navigation system.Based on the loose combination mode of the SINS/GNSS integrated navigation system,the algorithms which can improve the accuracy is investigated.(1)Research on sensor data preprocessing.In order to improve the accuracy of the Inertial Measurement Unit(IMU),the preprocessing of the output data of IMU is studied.Traditional wavelet threshold function data preprocessing algorithms suffer many problems,such as low precision of reconstructed signal and easy oscillation of reconstructed signal,etc.A new wavelet threshold function data preprocessing algorithm with reduced fixed deviation is proposed,which takes the advantages of soft and hard threshold function methods.Meanwhile,for the the problem that the wavelet threshold function method is difficult to do online data processing,a real-time wavelet threshold data preprocessing algorithm is designed based on the sliding window idea.Experimental results show that this method can denoise the IMU data in real time and improve the accuracy of the IMU data.Consequently,the accuracy of SINS is improved.(2)Research on orientation algorithm of integrated navigation based on ZHVC.In order to improve the orientation accuracy of integrated navigation system under the abnormal measurement noise,the orientation technology of integrated navigation system is studied.In order to solve the problems of the orientation low precision due to abnormal measurement signals and conventional model,an orientation algorithm based on Zero-Heading angle-Variational-Constraint(ZHVC)is proposed.In this method,the heading angle variation is used as the measurement information to extend to the traditional measurement vectors,and the attitude error equation is improved to enhance the observability of the heading angle.The estimation accuracy of the heading angle is improved and the influence of the GNSS measurement information on the heading angle estimation is reduced.In order to improve the estimation accuracy of the heading angle at turning,the dual models orientation algorithm are designed.Experiment results show that this method can effectively improve the accuracy of heading angle estimation.(3)Research on BBVI adaptive filtering algorithm based on Gaussian distribution.In order to improve the navigation precision of the integrated navigation system under the abnormal measurement noise caused by GNSS interference,the integrated navigation filtering estimation method is investigated.A Black Box Variational Inference(BBVI)adaptive filtering algorithm based on Gaussian distribution is proposed to solve the problem of hypothesis distribution in Variational Bayesian adaptive filtering.By analyzing the distribution of the time-varying measurement noise covariance matrix(MNCM),the prior distribution of the MNCM is assumed to be a Gaussian distribution,and the time-varying MNCM and state vectors are estimated by BBVI theory.Experiments show that the method can track the time-varying noise effectively when the GNSS signal is interference,and improve the accuracy of heading angle estimation effectivity.(4)Research on sequential adaptive filtering algorithm based on ABS.In order to improve the navigation precision of the integrated navigation system under the condition of interruption of measurement signal,the integrated navigation method of sequential filtering aided by Antilock Braking System(ABS)is studied.In order to solve the problem of low observability due to the limited measurement vectors provided by vehicle kinematics,and the loss of effective measurement information caused by the interruption of single measurement information of satellite navigation system,an integrated navigation algorithm based on sequential filtering assisted by ABS is proposed.In this method,the sequential adaptive filter is designed to improve the utilization rate of the effective high-precision measurement information and reduce the filtering calculation,so as to improve the navigation accuracy of the system.Experimental results show that this method can enhance the observability and improve the navigation precision of the system when the measurement signal is interrupted.