Research On Multi-GNSS Receiver Autonomous Integrity Monitoring Algorithm

With the rapid development of the Global Navigation Satellite System(GNSS)and the continuous expansion of its application scope,people pay more and more attention to the security of the navigation service provided by it.Especially for applications related to life safety,users require that GNSS not only provide basic location information,but also have the ability to monitor anomalies and alerts and measure the confidence of current navigation information.This capability is GNSS integrity.Integrity is directly related to the user’s positioning safety,and has become the most important GNSS performance indicator in the field of life safety such as civil aviation.In order to meet the stringent integrity performance requirements in civil aviation and other fields,GNSS integrity monitoring technology has emerged as the times require.At present,a system framework has been formed for basic navigation system integrity monitoring,external enhancement integrity monitoring,and user-end integrity monitoring.User-end integrity monitoring,also known as Receiver Autonomous Integrity Monitoring(RAIM),has become a research hotspot in the field of GNSS integrity monitoring due to its advantages of low cost,high efficiency and short alarm delay.As an early form of RAIM,the traditional RAIM algorithm is based on the assumption of a single fault observation,and is applied to the standard single-point positioning algorithm of the single-frequency single system,which can provide horizontal direction guidance for the aircraft in the non-precise progressive stage.The development of multi-frequency multi-system GNSS brings an opportunity for RAIM algorithm to support the precision approach phase with more stringent integrity requirements.However,the use of multi-frequency and multi-system observations greatly increases the probability of instantaneous multi-fault observations.Therefore,the RAIM algorithm under multi-frequency and multi-system must be able to deal with multi-fault situations.In this regard,relevant scholars extended the traditional RAIM algorithm to a high level and proposed the concept of ARAIM(Advanced RAIM)algorithm.Its initial goal is to support the LPV-200(Localizer Performance with Vertical Guidance-200)flight stage on a global scale and provide aircraft Vertical guidance service.At present,ARAIM technology is still immature,still in the research and testing stage of the algorithm,and has not yet reached the conditions for practical application.Build integrity monitoring stochastic models.However,the integrity support information parameters used in the existing ARAIM simulation tests are usually empirical values,which cannot accurately describe the true probability distribution of the signal-in-space ranging error,which is not conducive to the practical application of ARAIM;(2)For multi-fault detection and Recognition,the current algorithm has the problems of a large amount of calculation,a high false alarm rate,and a low recognition success rate,which reduces the continuity and integrity of the navigation system to a certain extent,and it is difficult to meet the real-time requirements of users;(3)In the integrity monitoring of high-precision positioning,there is a problem of incompatibility of the ARAIM algorithm.The ARAIM algorithm is adapted to the least squares parameter estimator,and the high-precision positioning represented by the precise point positioning PPP(Precise Point Positioning)usually uses the Extended Kalman Filter(EKF)estimator for positioning solution.The former only uses the current moment observation information for single epoch processing,while the latter needs to use the observation information of all epochs,so it is not suitable to directly transplant the ARAIM algorithm into the EKF filter.In order to meet the practical needs of users in the field of life safety for GNSS integrity,this paper systematically conducts relevant research on the technical problems faced by the above-mentioned receiver autonomous integrity monitoring algorithms.The main work and innovations include:(1)A normal distribution probability density function envelope model is proposed,which is applied to the estimation of ARAIM integrity support information parameters,and the validity of the estimated parameters is verified based on the measured data.In view of the problem that ARAIM integrity support information currently adopts empirical values and cannot truly describe the actual distribution of signal-in-space ranging errors,this paper firstly evaluates the accuracy of BDS-3/GPS signal-in-space ranging errors based on long-term historical ephemeris data.Its probability distribution characteristics are analyzed.According to the integrity risk assigned by the space signal segment,a normal distribution probability density function envelope model is established,which realizes the confidence envelope of the true probability distribution of the Signal-in-Space range error,thereby effectively determining the integrity parameter URA(User Range Accuracy),used to build a stochastic model for the integrity monitoring of the client;secondly,the envelope degree of the ARAIM protection level to the positioning error samples was calculated and analyzed by using the measured data of the station,thereby verifying the validity of the integrity parameters;finally,based on the estimated integrity support information,the availability of the BDS-3/GPS dual-system ARAIM in the global LPV-200 flight phase is evaluated,which provides an important reference for the research on the ARAIM algorithm compatible with the Beidou system.(2)An integrity monitoring method based on the quasi-accurate detection(QUAD)method is proposed and applied to the ARAIM algorithm to realize the detection and elimination of multi-faulty satellites.Aiming at the problems of large amount of calculation and low success rate in the multi-fault detection and identification algorithm of ARAIM,this paper proposes an integrity monitoring method based on the QUAD method.Accurate identification of multiple faults under epoch,and further integrity monitoring of parameter estimates after troubleshooting,thus improving the robustness of troubleshooting.Based on the theory of probability and statistics,the single-epoch integrity risk calculation method in the least squares solution is studied,and the purpose of quantifying the reliability of parameter estimation is achieved by determining the worst-case integrity risk under multiple failure modes.The integrity monitoring method based on the quasi-quasi-calibration method is applied to the ARAIM algorithm to achieve accurate detection and elimination of multiple faulty satellites,thereby effectively improving the continuity of real-time positioning and meeting the integrity needs of users in the field of life safety.(3)An integrity monitoring method suitable for the extended Kalman filter estimator is proposed,and it is applied to the precise single point positioning algorithm to ensure the integrity of the high-precision positioning.In view of the problem that the ARAIM algorithm is not suitable for EKF and cannot provide integrity for high-precision positioning users,this paper proposes an EKF integrity monitoring method that can take into account the impact of all potential faults in history.By introducing the monitoring form of time window,the fault detection under multi-epoch is realized,and the problem that the calculation amount of the algorithm increases with the increase of processing time is solved.By conservatively introducing the forecast value deviation in the integrity risk assessment,the fault vector in the worst case is determined,which ensures that the algorithm is robust to potential faults before the window,so that it can be applied to high-precision positioning integrity for a long time.In addition,this paper applies the EKF-based integrity monitoring method to the precise single point positioning algorithm,and verifies the effectiveness of the method through simulation and actual measurement experiments.