Research On Satellites Multi-fault Detection And Identification Algorithm At Receiver

In order to ensure that the navigation system can serve aviation users reliably,it is necessary to monitor its integrity.In the integrity monitoring method,the receiver autonomous integrity monitoring algorithm is widely used because of its lack of external information and high autonomy.However,the receiver autonomous integrity monitoring algorithm still has problems such as low failure detection rate,low recognition rate,and no data preprocessing.On the basis of further research on receiver integrity monitoring algorithm,this paper introduces ISC parameters to improve RAIM algorithm fault detection and recognition rate,combines the gross error detection method with MHSS ARAIM to solve the problem of no data preprocessing.The main research contents and innovations of this paper are as follows:(1)Based on the introduction of pseudorange location principle,the Receiver Autonomy Integrity Monitoring algorithm is studied.This paper analyzes the least-squares residual method and parity vector method in Receiver Autonomy Integrity Monitoring(RAIM)algorithm,and deduces and verifies the two methods are equivalent.The three algorithms of Relative RAIM(RRAIM),Carrier RAIM(CRAIM),and ARAIM algorithm of Multiple Hypothesis Solution Separation(MHSS)are studied in Advanced Receiver Autonomy Integrity Monitoring(ARAIM)algorithm.The disadvantages of each algorithm are compared and analyzed.(2)In order to explore the effect of new ISC parameters on the RAIM in GPS civil ephemeris,this paper introduces ISC parameters into the RAIM algorithm,uses GPS data for testing and analysis.The experimental results show that the introduction of ISC parameter correction can improve the accuracy of the error in unit weights,reduces the thresholds of RAIM algorithm,and further improves RAIM performance.(3)Aiming at the problem that the MHSS ARAIM algorithm does not preprocess the original data,this paper presents a MHSS ARAIM algorithm based on gross error detection,and uses GPS and BDS observations to detect gross errors.The test and analysis results show that the gross error detection method can effectively remove the gross error of more than 20 m,and the performance of the new algorithm is better than MHSS ARAIM algorithm.(4)The BDS,GPS,and GLONASS observations were used to analyze the sound performance of the MHSS ARAIM during the LPV-200 precision approach.The test results show that the performance of the multi-system MHSS ARAIM algorithm is better than that of a single system,and provides better navigation services for aviation users.