Research On Receiver Autonomous Integrity Monitoring In Typical Urban Canyon And Simulation System Design

As one of the most important service performances,integrity provides a reliable and guaranteed result for satellite navigation system.Receiver Autonomous Integrity Monitoring(RAIM)is an effective integrity monitoring method.It could rapidly respond to satellite faults,completely independent,low cost,and can also provide users with the alarm information promptly and effectively.Traditional RAIM methods are designed based on the assumption that the Code Noise and multipath(CNMP)obeys the Gaussian distribution.With the development of the global navigation satellite system(GNSS)and its more extensive application scene,the application of integrity monitoring in non-Gaussian CNMP environment has become an important research focus.In urban canyon environment,the signal sheltering and reflections lead to a large amount of non-Gaussian CNMP.Meanwhile,the number of visible satellites is greatly reduced due to a wide range of shelters.These two aspects decrease the accuracy of the RAIM significantly,and have an influence on navigation system application.Taking typical urban canyon(TUC)as the application environment,the RAIM technologies are researched in this paper.The main research contents in this thesis include the following aspects.Four TUC CNMP collecting schemes are designed,including observation station,smallscale shelter static scene,large-shelter static scene and low dynamic test scene.The distribution characteristics of real CNMP in different scene are collected and analyzed respectively.The analytical results show that there is a stronger non-Gaussian in the larger shelter scene.And the CNMP in the dynamic test scene show stronger non-Gaussian than that in the static scene.Based on the analytical results,two distribution models are proposed.The CNMP distribution model considering both orbit type and elevation angle is proposed for Beidou Navigation Satellite System(BDS),which can improve the estimation accuracy of the CNMP distribution.And then a dynamic Gaussian expansion distribution model is designed to describe the CNMP distribution in TUC.It can effectively monitor the CNMP changes,dynamically adjust the expansion coefficient and then improve the estimation accuracy of the CNMP distribution model.With the distribution models,three RAIM methods are proposed for the integrity risk,non-Gaussian CNMP and fault processing in TUC according to the research of RAIM.To reduce the integrity risk,a slope-weighted least squares RAIM method is proposed.It can reduce the undetected probability and false alarm probability.For non-Gaussian CNMP,a modified unscented Kalman filter particle filter(MUKF-PF)is proposed,which improves the sensitivity of fault detection and take less workload of UKF.To avoid low positioning accuracy due to satellite isolation,the residual estimation Bayes RAIM and gross error correction fault processing method is proposed.It can effectively monitor multiple-satellite faults in non-Gaussian environment,and correct the gross errors with estimating value,ensuring the positioning accuracy in TUC.The availability of RAIM in TUC is researched.The protection level(PL)of slopeweighted least squares RAIM is deduced.Then the availability is analyzed in Asia service area which is constrained by different shelter elevation angles for simulating the urban canyon environment.In addition,the availability is also analyzed in small-scale shelter and largescale shelter static test scene.With the requirement of positioning accuracy and availability,a satellite-selection method based on availability is proposed,which ensures positioning accuracy and improves RAIM availability.An extendible RAIM simulation system for researching in TUC is designed,which realizes the mathematical simulation for new models and methods of TUC scene,RAIM and so on.A simulation model intelligent recommendation method based on incidence relation and a recording framework based on resource description are proposed in this system,which increases the efficiency of the simulation task flow design.