Research On The Algorithms Of Integrated Train Positioning Based On BDS/INS

With the rapid development of railway transportation in China,more and more att ention has been paid to the safety of train operation and train position.As the satellit e navigation system and inertial navigation system(INS)are complementary in functio n,which can effectively improve the performance of the train positioning system,it h as been the focus of research at home and abroad.The research on the information fu sion technology of integrated navigation system has become the key link to improving the positioning accuracy of the integrated navigation system.In the application of train positioning,China's Beidou satellite navigation system(BDS)gradually improve makes the research on information filtering technology of BDS/INS integrated navigation sys tem a very important strategic and forward-looking significance.This paper made the Beidou satellite navigation system and inertial navigation system as backgroud and analyzed the characteristics of Extended Kalman filter(EKF)? Unscented Kalman filter(UKF)and Particle filter(PF)in detail.Aimming at the problem that particle filter algorithm is prone to lacking of diversity of particle samples,we designed a new algorithm—ACO-PF,which combined with ant colony algorithm.The ant colony algorithm which using the characteristics of the distributed parallel search was used to optimize the resampling process before the update of particle state and alleviated the lack of particle samples.In order to assess the effectiveness of ant colony optimized particle filter algorithm,we established a mathematical model and tested these algotithms.The results show the advantages of improved particle filter algorithm in processing nonlinear problems.In the end,according to the error parameters of BDS/INS,a mathematical model of train speed error,position error,gyro and accelerometer is established.The UKF,PF and ACO-PF algorithms are applied to train error model and the MATLAB simulation results show that the improved algorithm got a better performance in filtering.The simulation results proved that,comparing with the conventional particle filtering,the modified particle filtering can improve the diversity of particles which makes the particles closer to actual values.And it improved the stability and positioning accuracy of the combined navigation system,providing a guarantee for the safe operation of train.