Research On Satellite Selection And RAIM Availability Of Beidou/GPS Dual Mode Navigation Receiver

The multi-constellation satellite selection algorithm and the RAIM algorithm is continuously developed along with the construction of the global navigation satellite systems.In order to ensure the navigation system real-time positioning,the satellite selection algorithm roughly judges the distribution of visible satellites before positioning,and selects a subset to perform the positioning solution.RAIM,the receiver autonomous integrity monitoring,is an algorithm included in the receiver to ensure positioning reliability.This thesis is devoted to solving the practical problems faced by multi-constellation satellites navigation and positioning,and conducts in-depth research on two aspects: multi-constellation satellite selection and RAIM availability.Firstly,the relationship between satellites' space geometry structure and GDOP is analyzed,and the principle of traditional RAIM fault detection and recognition is introduced.Then,two problems(quickly select the visible satellite subsets and particle filter RAIM availability and improvement method)are discussed,the algorithm model is established,and the group intelligent optimization algorithm is used to improve method,the specific research contents are as follows:(1)Firstly,the calculation methods and characteristics of GDOP(geometric dilution of precision)for integrated navigation are analyzed.Two common methods of fast satellite selection based on the minimum GDOP are introduced.Through the experimental simulation,the relationship between GDOP and the number of visible satellites is obtained.Then,the principle and operation process of the satellite fault detection and isolation algorithm are described in detail.(2)For quickly and effectively selecting the visible satellite subsets for positioning,a satellite selection algorithm based on particle swarm optimization is proposed,PSO satellite selection algorithm model is established,and the influence of algorithm parameters on the results of satellite selection is analyzed.Experiments show that this method can quickly realize satellite selection for BDS and GPS dual constellation,which provides a new idea for the fast satellite selection method.(3)Based on the basic PSO satellite selection,the particle population is initialized by chaotic mapping,and the time-varying inertia weight and acceleration coefficient with the number of iterations are used to optimization algorithm.In addition,in order to ensure the diversity of particles in population,the 20% particles with good performance are retained in the process of satellite selection,and the remaining 80% of the chaotic search initial solution space is used to replace the particles with poor performance.Experiments show that the improved PSO fast satellite selection algorithm can effectively improve the instability of the algorithm,but the time spent on the satellite selection has increased.(4)The receiver autonomous integrity monitoring(RAIM)method based on chaotic particle swarm optimization-particle filter(CPSO-PF)algorithm is proposed.The algorithm model is established,the availability of the algorithm is judged,and if the algorithm is available,fault detection is performed.Finally,the algorithm is validated by real navigation data,and it is concluded that the algorithm is available and can effectively detect and isolate satellite faults under non-Gaussian measurement noise conditions.