Research On BDS/MEMS IMU Deep Integrated Navigation Technology And High Performance Algorithms

The status and role of the new strategic weapon in the high-tech war is becoming more and more prominent.Compared with the traditional weapon system,the new strategic arms such as the strategic missile defense,military aerospace,space maneuvering platform and global rapid strike need realize higher,farther and faster attack.The performance of weapon navigation system has higher requirements.This situation promotes the research of integrated navigation method.Among all kinds of integrated navigation system,GNSS/INS integrated navigation mode is one of the integrated navigation modes which are most widely used.The INS which has strong autonomy and short positioning accuracy can provide a three-dimensional position,velocity and attitude and other navigation information.With the time increasing,the INS navigation error will accumulate.GNSS has an advantage of the high positioning accuracy and the merit which is convenient.However,GNSS depends on the artificial beacon and is vulnerably disturbed by the human,which can not achieve full autonomy.Therefore,the combination of INS and GNSS can make the precision and reliability of the integrated navigation system greatly improved by the combination of these two complementary systems.Deep combination technology is a research hotspot in the field of integrated navigation,and it is also the development trend of integrated navigation technology.With the Beidou satellite navigation system officially entering the construction phase,the study of BDS/MEMS IMU depth integrated navigation technology,not only provides the technical reserve for micro integrated navigation system of the development of China with independent intellectual property rights,but also have important significance to the development of information weapon equipment.In this paper,the key technologies and high performance algorithms of IMU BDS/MEMS deep integrated navigation are studied.The main results are as follows:(1)The current situation and development trend of integrated navigation are studied.The advantages and disadvantages of several different integrated navigation modes which included the loose combination of navigation,the tight combination of navigation and the deep combination of navigation mode are analyzed.The data processing technology of INS navigation system,the data processing technology of BDS navigation system and the error source of the Beidou system and the compensation method are studied.(2)The paper establishes the BDS/MEMS IMU deeply integrated navigation system principle,system structure and mathematical model.The BDS/MEMS IMU deep integrated navigation system software design method and the deeply integrated navigation software process are given.A BDS receiver vector tracking loop structure is built.Finally,the paper completes the BDS/MEMS IMU deep integrated navigation system simulation,and proves correctness and effectiveness of the system principle,system structure and mathematical model which are designed in the paper.(3)A random weighted Sage adaptive filtering method is proposed.According to the different influence degree of residual vector,innovation vector and the state correction number on the accuracy of Sage filter,this method uses the random weighted method to estimate the innovation vector,the residual vector and the state corrections parameter and obtains the noise covariance matrix and the noise covariance matrix of the system state.The random weighted method can estimate the observation noise covariance matrix and noise covariance matrix of system state estimation and improve the dynamic filtering accuracy.Finally,the proposed algorithm is verified by simulation.(4)An adaptive filtering algorithm based on noise limited memory is proposed.The moving window technique and random weighting estimation are combined.The system measurement noise and system noise statistics using moving window method are obtained.The system measurement noise and state noise statistical characteristics are online random weighting estimated by the random weighting method.According to the size of the error,the random weighted adaptive factor effect of control system is adjusted to control the solution precision's influence which caused by the measurement noise and state filtering noise.Finally,simulation experiments are carried out on the proposed algorithm.(5)The structure and the principle of the BDS/MEMS IMU Deep Navigation prototype are designed,the system software structure and the system workflow are built,the experimental test and the specific content of the prototype demonstration are given,the data involved by the thesis,theoretical achievement,model,algorithm and calculation software are verified and implemented.The research achievements of this paper have a certain contribution for the navigation positioning and the filtering solution of the new strategic weapons which are represented by the strategic missile defense,military aerospace,space maneuvering platform and the global quick strike.The research results through the promotion can also be used in the other aerospace aircraft navigation and filtering solution.