Research On Digital Electronic Map Aided BeiDou/INS Train Combination Positioning Method

With the rapid development of science and technology,more stringent requirements are placed on the train positioning technology.The single navigation and positioning technology can not meet the precise positioning of the train.With the completion of China's Bei Dou satellite network in 2020,the conditions for applying the satellite integrated navigation and positioning system to the train positioning technology of China's medium and low-density railway lines have gradually matured.By further improving the navigation and positioning equipment of existing trains and meeting the requirements of higher speed trains for positioning accuracy,it is the development direction to further ensure the safe and stable operation of trains.The thesis focuses on the key issues of the train combination positioning system,and proposes to improve the output precision by changing the elliptical angle in the optical cavity structure of the " ? " type cavity.Bei Dou weak signal studies the capture and tracking algorithm.Based on the multi-source combination method,the digital electronic map aided BDS/INS navigation train integration strategy is proposed,MLAUKF filtering algorithm of BDS/INS train self-positioning for DEM is proposed,which realizes the optimization of positioning algorithm and the effective data fusion of information.The dissertation proposed algorithms of BDS/INS train positioning,which main contributuins and innovation are as follows:(1)Aiming at the low output precision of the fiber optic gyroscope under the train vibration base,the internal structure of the "? " type cavity is designed.By adjusting the tilt angle of the elliptical structure of the cavity,the Fano resonance effect is effectively controlled,which is improving the fiber optic gyroscope,accelerometer layouts and array maps were designed.The noise type of accelerometer is analyzed,and the Kalman filter denoising method based on wavelet transform is proposed.(2)Based on the in-depth analysis of the circular correlation zero-padding mechanism,combined with the idea of fast search random tree,an improved FMDBZP algorithm based on the weak signal acquisition method of Bei Dou navigation receiver is proposed.The algorithm establishes the navigation data bit screening mechanism of random tree search,and finally obtains the most possible navigation data bit result by quickly searching the planning path of the random tree to obtain the optimal path search result,thereby achieving the purpose of reducing the calculation amount,and The invention solves the shortcomings of the calculation between the number of points in the block and the number of input points of the Fourier transform.The result shows that the acquisition method can further reduce the amount of calculation and improve the satellite signal acquisition of the Beidou receiver without sacrificing the acquisition accuracy and speed.(3)An adaptive tracking algorithm for the tracking loop Bei Dou signal based on EKF filtering algorithm is proposed.The EKF filtering algorithm is constructed by taking the correlation value of the loop as the observation,and the state feedback control is performed by using the output filtering estimator.The algorithm can adapt to the change of Bei Dou signal strength during the train trajectory process,and can accurately track the signal changes of Bei Dou weak signal and high dynamics during train operation,thus effectively controlling tracking error and adaptively adjusting the equivalent noise bandwidth of the loop,to ensure the stability of the Bei Dou signal.(4)Aiming at the BDS/INS train positioning model,an adaptive UKF filtering algorithm for BDS/INS deep combined train positioning based on maximum likelihood criterion is proposed.Firstly,the posterior probability density of the measurement vector is constructed by using the statistical information of the innovation vector,and then the process noise variance is estimated online by the maximum likelihood criterion and fed back to the UKF filtering process,which is adjusting the Kalman filter gain.The proposed algorithm is an adaptive filtering method with process noise variance estimator,can suppress the influence of process noise variance uncertainty on the filtering solution,online estimation and adjustment process noise statistics,suppressing the influence of its uncertainty on the navigation solution,enhancing the adaptive ability of the algorithm under dynamic conditions,and improving the estimation accuracy of the parameters.According to the principle of modularization,the Beidou capture and tracking integrated software was designed.The correctness and reliability of the capture and tracking algorithm were verified by the Beidou satellite hardware module.Digital electronic map assisted BDS/INS train self-positioning integrated software to verify the feasibility of the proposed algorithm.The paper mainly completed the train running track,the INS error analysis of the train moving base,the capture and tracking of the Beidou signal,the establishment of the self-positioning model and the performance simulation of the MLAUKF filtering algorithm.At the same time,through field experiments,the results show that the digital map-assisted BDS/INS train self-positioning can realize the precise positioning of the train under the Beidou weak signal,and the research results can provide some reference for the application of the integrated navigation and positioning technology in the train operation control system.