Research On Multi-band Fusion Positioning Method And Application Based On BDS

Bei Dou navigation satellite system(BDS)is a global satellite navigation system(GNSS)independently developed and operated by China to meet the needs of national strategic security and social and economic development.By December 2019,the BDS III had been basically completed and prepared to provide services to the world.In the past two years,BDS has successively released the spatial signal interface control documents of three frequency bands of B2A(replacing the original unstable B2I),B1 C and B3 I.In addition to the traditional B1 I band,users can receive the public signals of four frequency bands at present,making it possible for BDS to take multiple frequency bands fusion positioning.Compared with the positioning based on single band satellite signal,multi band fusion positioning has the advantages of high positioning accuracy,strong positioning stability and wider coverage,so it has become a research hotspot in the field of international satellite navigation in recent years.In order to further improve the accuracy and stability of BDS standalone positioning,in this thesis,the research on the multi-band fusion positioning method and its technical application of BDS is carried out.The nonlinear Kalman filter algorithms including extended Kalman filter(EKF)and unscented Kalman filter(UKF)are the more commonly used position estimation algorithms for global navigation satellite system.However,the calculation of EKF is complex,and the estimation results will be divergent for the highly nonlinear system.In UKF,the covariance matrix may not be positive definite,which leads to the process of iteration process can not flow normally.In this thesis,based on UKF,the square root form of covariance matrix of state quantity is used for iterative calculation in the filter.That is,square root UKF(SRUKF)algorithm to ensure the stability of iterative process and state update.Because the filtering algorithm needs to determine the covariance matrix of process noise and measurement noise firstly,which is easily affected by environmental factors and difficult to be accurately obtained,thus restricting the application of SRUKF algorithm.This thesis introduces ant colony optimization(ACO)algorithm is used to effectively determine the noise covariance,and a new location estimation algorithm(ACO-SRUKF)is proposed in combination with SRUKF to further optimize the filtering performance,and the superiority of this algorithm in BDS position estimation is verified by experiments.Because the multi-band signal fusion positioning is based on the same satellite,more observation values can be obtained so as to establish a model to offset the ionospheric delay in the process of signal transmission,which has the advantages comparing to single band standalone positioning,so as to obtain better positioning results.In this thesis,based on ACO-SRUKF algorithm,B1 I and B3 I signals are selected to perform multi-band fusion positioning.The experimental results show that the proposed method can perform higher positioning accuracy and stronger stability.This study can provide theoretical basis for BDS multi-band fusion positioning method,and provide technical reference for expanding application scenarios,optimizing use mode,improving positioning performance,strengthening safety and controllability.