Research On Positioning Model And Algorithm Of Train Muti Source Information Fusion Based On BDS/INS

As the global navigation satellite system(GNSS) and inertial navigation system(INS) can be used to complement each other, it has a very broad application prospect, so the reliability and accuracy of navigation system has been a hot point in the field of domestic and foreign navigation research. Data fusion filtering technology is an important direction in the application of GNSS/INS integrated navigation system. Navigation application study is an important direction to filter data fusion technology, application of this technology can improve the accuracy and reliability of integrated navigation system.At present, China’s Beidou satellite navigation system(BDS) has been put into use and is gradually improving, integrated navigation system based on BDS and INS composed of multi source information fusion positioning applications, the development of China’s high-speed rail, with a very broad range of forward-looking, practical and strategic significance.This paper is based on the CTCS3 control system, after analyzing and comparing the two kinds of navigation systems of BDS and INS, a multi source data fusion and positioning model based on BDS and INS is established. The paper builds a multi source data fusion and positioning model based on BDS and INS. The paper is based on and INS. For the standard Calman filter(KF) and the improved extended Calman filter(EKF),(UKF) and particle filter(PF), a new algorithm based on UKF and PF is proposed, which is based on and MUPF. In order to effectively verify the performance of MUPF filter algorithm in integrated navigation system, this paper will carry out the common filtering algorithm and MUPF algorithm in the simulation model, and use MATLAB tool to simulate the simulation results. Through the analysis and comparison of the simulation results, it shows that the improved MUPF algorithm can effectively solve the problem of the positioning accuracy. Compared with other filtering algorithms, it can adapt to the BDS/INS integrated navigation system, and greatly improve the stability and accuracy of the train integrated navigation system.