The Research On BDS/GNSS Maritime Precise Point Positioning And Integrity Monitoring

Precise Point Positioning(PPP)is widely used in maritime positioning applications,because of its advantages of high-precision positioning on a global scale with a single receiver.At present,the maritime PPP applications is mainly based on Global Positioning System(GPS),which is limited by long convergence time and difficult to guarantee reliability.Therefore,how to improve the accuracy and reliability of BDS/GNSS maritime PPP is a key issue must be solved.This thesis studies on the BDS/GNSS real-time maritime PPP processing,data quality control,rapid convergence and integrity monitoring,which aims to improve the accuracy and reliability of real-time maritime PPP to meet high precision and high reliability requirements.Finally,it is expected to lay a solid theoretical and practical foundation for the future development of real-time maritime PPP.The main innovative research of the thesis is as follows:(1)The processing method of BDS/GNSS real-time maritime PPP is summarized systematically,including error correction models,mathematical models,and estimation methods.Subsequently,a preliminary structure of BDS/GNSS real-time maritime PPP is promoted and established.On this basis,the positioning performance of BDS and BDS/GNSS real-time maritime PPP is evaluated for the first time.The results show that BDS has lower position accuracy and slower convergence time than GPS.Meanwhile,the integration of BDS,GLONASS and GPS significantly improves the position accuracy and the convergence time.Some outliers in the single constellation configuration can be mitigated when multi-constellation observations are utilised.(2)In order to ensure the consistency of real-time maritime PPP between the function model and the stochastic model,the quality control methods of real-time product data age,ionospheric anomaly,and gross unmodel errors were studied.Firstly,the stochastic model relating to the ages of real-time products is established to improve the PPP convergenced position accuracy when the real-time products are interrupted.Secondly,A two steps approach is proposed by integrating the cascaded linear time invariant low-pass filters with adaptive Kalman filter.It constructs a new test statistic to detect anomaly ionospheric gradient.Compared with the traditional CCD methods,the estimation accuracy of ionospheric gradient and the response time to ionospheric gradient are improved simultaneously.Finally,regarding to the issue of the gross unmolded errors,a robust sequential least squares(RSLSQ)is proposed based on IGG-? model.Compared with SLSQ,the convergence time of RSLSQ improves and some outliers in SLSQ configuration can be mitigated.(3)In order to reduce the convergence time of PPP,the spherical cap harmonic(SCHA)analysis is introducted into the model construction of the regional tropospheric delay,and the solution method and the properties of the spherical cap harmonic function are studied and deduced.Compared with the traditional PPP,the convergence time of SCHA augmented PPP improves.The re-initialization of PPP can be avoided by cycle slip detection and correction.Ionospheric delay is critical for cycle slip detection and correction,especially for a long data gap.The proposed method constructs the extra-wide lane(EWL),the wide lane(WL),and the narrow lane(NL)epoch-defferenced linear combinations based on the ionosphere constrain criterion,so as to determine the undifferenced cycle slips from the cascading ambiguity resolution.The results show that the cycle slips can be fixed correctly even though cycle slips occur in all the available carrier phase observations,and longer data gaps can be merged without continuity loss.Furthermore,the instantaneous re-initialization can be achieved with the proposed method.In addition,a multi-receiver ambiguity association method based on the zero baseline constraint is proposed to slove the re-convergence problem in PPP applications due to the GNSS signals interruption.The method establishes the relationships of ambiguities between different receivers.The results show that the re-initialization can be achieved in single epoch.(4)Receiver autonomous integrity monitoring is an important means to ensure the reliability of PPP.Firstly,an advanced protection level related to the random error and the constant deviation is constructed to improve availability.Secondly,the traditional PPP integrity monitoring method based on Kalman filter usually assumes the state and observation models are correct,while the significant deviatins from the assumed models for systems may also occur.A sequential PPP integrity monitoring based on SLSQ is proposed by introducing virtual observations to monitor measurements and modeling failure,and the proposed method avoids the continuity loss caused by incorrected predicted model.