The Research On GNSS Integrity Monitoring Under Multi-Scenarios

This paper expended discussion around the research on GNSS user integrity monitoring under multi-scenarios. By taking focus on integrity monitoring technology of BeiDou satellite navigation system(BeiDou), comprehensive analysis of user integrity monitoring methods and performance were implemented based on theoretical derivation and diverse experimental under different scenarios, such as single system, multiple systems, system failure, shelter environment, and other user auxiliary information.The result provided theoretical and practical basis for BeiDou system user integrity monitoring technology. The major contributions of this research are summarized as three parts: " Mixed constellation positioning method", "User Receiver Autonomous Integrity Monitoring(RAIM) methods", "User Information Assisted GNSS Integrity Monitoring methods".(1)The generation principle and estimation methods of system time offset, which is considered as one of main error sources in mixed constellation na vigation, is firstly discussed. Then, according to the way of estimation of system time offset, mixed constellation positioning algorithm is distinguished in two levels : system level algorithm and user level algorithm. A detailed analysis of positioning characteristics of these two types of positioning algorithm under different scenarios is processed. Furthermore, system time offset Assisted is introduced to assist system level GNSS positioning on mixed constellation. This positioning algorithm can effectively use the system time offset information, which is a modified form of the traditional system level positioning algorithm. Tests showed, with assisting of system time offset, the positioning algorithm owns higher availability in multi-block area.(2)In this paper, comprehensive assessment on the performance of RAIM of BeiDou / GPS is assessed under various scenarios. On one hand, according to the step of user integrity monitoring, some indicators are defined: integrity availability, reliability and recognizability. Each index characteristics are evaluated. On the other hand, based on quality control theory, GNSS RAIM per formance evaluation strategy is established. Moreover, BeiDou / GPS RAIM performance is testified throughout various test scenarios. Test results show that: 1) deviation of BeiDou constellation can be monitored in about 5m; 2) strong correlation exists between pairs of measurements; 3) the undetected error may affect on the direction of greater elevation; 4) mixed constellation could enhance system reliability and reduce the measured correlation between pairs of observations. The evaluation results provide practical meaning for BeiDou system integrity monitoring techniques.(3) Two user information assisted integrity monitoring method are proposed, which are system time offset assisted integrity monitoring method(TOAIM) and receiver clock error assisted integrity monitoring(C EAIM). For the purpose of evaluation, by defining two performance indicators, fault detection rate and fault identification rate, the performance of TOAIM and CEAIM are testified. As for TOAIM, based on the stability and accuracy of system time offset monitoring technology, the deviation between current monitoring and predicted values of system time offset is introduced. A detailed description of the key steps of TOAIM are involved, including system time offset prediction method, fault detection method, threshold determination and fault identification method. Assessment results show that TOAIM could be used in mixed constellation(multi- system) case, in which case 1) the greater the failure, the high possibility the system can detect and successfully identify the fault observations; 2) increase in ambient occlusion, fault detection and fault identification rate may improve; 3) the maximum likelihood estimation may suitable for fault identification step; 4) with the error more than 150 m, the fault detection rate and fault identification rate could reach 90% or even better; 5) the height of satellites has little effect on the TOAIM performance. As for CEAIM, based on the stability and accuracy of the receiver clock error, the deviation between current resolving and predicted values of receiver clock error are introduced. Four major steps, which are clock error receiver prediction model selection(quadratic polynomial, Kalman filtering, AR(p)), fault detection method, the threshold determination and fault identification method are discussed. Assessment results illustrate that CEAIM could show better performance of integrity monitoring in single system than in multi-system, in which case 1) Kalman filter with 10 historical data seems show better prediction of receiver clock error; 2) threshold is significant for the algorithm performance. The threshold elevation with cut-off angle changing; 3) for single system, the maximum likelihood estimation method is suitable unser open environment, while subset comparison law applies to shelter environment.