Research On GNSS Multi-frequency And Multi-system Autonomous Integrity Monitoring And Signal Quality Analysis Technology

Due to the increase of the Global Navigation Satellite Systems(GNSS)constellation,more visible satellites participate in the positioning service,so the positioning accuracy has been improved.But at the same time,the signal quality problem under multi-satellite positioning has become more sensitive.Abnormal GNSS signals will affect the normal operation of ground navigation and positioning systems,and even weaken life safety service levels.Through the quality assessment of the navigation signal,the operating status and service quality of the satellite in orbit can be inferred,and the uncertain factors of the propagation environment can also be reflected.Therefore,a reliable assessment of signal quality is one of the necessary conditions to ensure that the terminal fulfills various service requirements.In order to obtain more accurate GNSS signals and provide more reliable satellite services,this article focuses on GNSS multi-frequency and multi-system autonomous integrity monitoring and a signal monitoring network from point to surface.In this paper,the main contributions are as follows:1.The Advanced RAIM(receiver autonomous integrity monitoring)is performed performance analysis on Non-classical GPS and BDS combined constellation.Compared with the simulation data used in most literatures,this paper uses real data of station for GPS/BDS analysis.At the same time,due to the characteristic nature of BDS in the Asia-Pacific region,the theoretical simulation time used by the algorithm was analyzed and verified,and a new constellation configuration based on the GPS/BDS combined constellation in the Asia-Pacific region was proposed and verified to make it more approximate ARAIM performance under real conditions.2.ARAIM algorithm for maximum approximation is proposed.Aiming at the problem of insufficient optimization of ARAIM's allocation of configuration information probability,this paper improves ARAIM performance by reducing the difference between the two most important view solutions affecting the VPL(vertical protection level)and the all-in-view solution while satisfying the accuracy.The results show that for the depleted constellation in the case of visible satellite reduction,the coverage can increase from 59.97% to 76.63%with the assistance of improved ARAIM.Even for the optimistic constellation,where there is not much room to improve availability,the improved algorithm can increase the coverage to approximately 3%.3.ARAIM algorithm based on feedback structure is propose.The classic ARAIM algorithm only satisfies the minimum error under the nominal conditions,and the difference of the combined weight will affect the calculation of the protection level.The feedback ARAIM algorithm can calculate the most accurate weight solution under the current threshold.By improving this small difference,the VPL in most areas is reduced to less than 35 m.4.Aiming at the situation that eye diagrams and constellation diagrams require human participation in order to identify abnormalities,a visual monitoring model is proposed.Through long-term normal data collection and classification,the threshold is concretized into a rule forbidden zone.Autonomous judgment is made by whether there is data mapped out by the signal in the restricted area of the rule.