Research On Autonomous Integrity Monitoring Method Of Train Integrated Localization For Railway Applications

With the rapid development of high-speed railways,the traditional train localization method relying on track-side equipment is changing towards "train-centered" continuous localization.The integrated train localization based on Global Navigation Satellite System(GNSS)and Inertial Navigation System(INS)is the research trend of the Next Generation Train Control System(NGTC).It is of great significance to study the performance of the integrated localization algorithm through its accuracy and integrity in complex railway scenarios,with regards to the train movement characteristics as “track constraint,given routing”.Based on the pseudorange error estimation model using satellite elevation angle and carrier-to-noise-density ratio,the thesis first studies the weighted tightly-coupled localization algorithm based on Extended Kalman Filter(EKF);secondly,it studies the INS assisted integrity monitoring algorithm for railway complex environments,improves the correctness and availability of algorithm in railway applications;finally,to effectively evaluate the availability of the integrity monitoring algorithm,a digital track map(DTM)assisted integrity monitoring availability identification method is studied.The contributions of this thesis are as follows:(1)The GNSS/INS weighted tightly-coupled localization algorithm based on EKF is studied.The satellite elevation angle and carrier-to-noise-density ratio affected pseudorange error estimation model are used to establish a weighting matrix,and the weights of satellite observations in the positioning solution are reasonably allocated to improve the accuracy and robustness of the algorithm.(2)For observation scenarios with sufficient number of visible satellites,to optimize the INS Assisted Integrity Monitoring(IAIM)algorithm,a weighted EKF for Weighted INS Assisted Integrity Monitoring(WIAIM)algorithm is proposed;For observation scenarios with insufficent number of visible satellites,a robust IAIM algorithm based on Danish method is proposed,re-weighting the pseudorange observation error corresponding to the fault satellite.On one hand,it can resist the larger positioning error.On the other hand,it can keep observation redundancy when there are insufficent number of visible satellites.(3)Analyze the parameters of integrity monitoring availability identification method,give an optimal identification method based on EKF innovation variance.Combined with the digital track map(DTM),a DTM-assisted integrity monitoring availability identification method is proposed.The DTM data is applied to match the train position estimated by the INS to the track,and accurately predict the pseudorange value to optimize the availability identification method performance.The thesis uses the weighted tightly-coupled algorithm to process the measured data collected by the Beijing-Shenyang high-speed railway line to evaluate the positioning accuracy and robustness of the algorithm.In addition,multiple sets of experimental scenarios were constructed from the measured data,and the performance of the integrity monitoring algorithm and the integrity monitoring availability identification method were compared and analyzed in different scenarios.The experimental results show that the positioning accuracy of the weighted tightly-coupled algorithm based on satellite elevation angle is improved by 1.3 meters to 2 meters.The two integrity monitoring algorithms proposed in this paper can correctly detect and identify single-satellite and dual-satellite failures.DTM-assisted integrity monitoring availability identification method has a low false alarm rate,which provides guarantee for the accuracy and availability of train localization in complex railway scenarios.Figure 73,table 17,reference 68.